Miracle-dz/UniFAR-FTUs huggingface dataset:
Run-time Estimates for Protein Folding Simulation in the H-P Model

The hydrophobic-hydrophilic (H-P) model for protein folding was introduced by Dill et al. [6]. A problem instance consists of a sequence of amino acids, each labeled as either hydrophobic (H) or hydrophilic (P). The sequence must be placed on a 2D or 3D grid without overlapping, so that adjacent amino acids in the sequence remain adjacent in the grid. The goal is to minimize the energy, which in the simplest variation corresponds to maximizing the number of adjacent hydrophobic pairs. Although the model is extremely simple, it captures the main features of the problem. The protein folding problem in the H-P model is NP-hard in both 2D and 3D. Recently, Fu and Wang [9] proved an exp(O(n1−1/d) · lnn) algorithm for d-dimensional protein folding simulation in the HP-model. Our preliminary results on stochastic search applied to protein folding utilize complete move sets proposed by Lesh et al. [15] and Blazewicz et al. [3]. We obtain that after (n/δ)c·Γ Markov chain transitions, the probability to be in a minimum energy conformation is at least 1− δ, where n is the length of the instance, Γ is the maximum value of the minimum escape height from local minima of the underlying energy landscape, and c is a (small) constant. Γ depends on the move sets, and future research will focus on upper bounds of this value. To be competitive with the Fu/Wang bound, Γ ≤ n1−1/d is required. From previous experiments on stochastic search applied to computationally hard problems [20] we expect Γ to be much smaller for real protein sequences.
Information propagation for interacting-particle systems

We study the speed at which information propagates through systems of interacting quantum particles moving on a regular lattice and show that for a certain class of initial conditions there exists a maximum speed of sound at which information can propagate. Our argument applies equally to quantum spins, bosons such as in the Bose-Hubbard model, fermions, anyons, and general mixtures thereof, on arbitrary lattices of any dimension. It also pertains to dissipative dynamics on the lattice, and generalizes to the continuum for quantum fields. Our result can be seen as an analog of the Lieb-Robinson bound for strongly correlated models.
An Algorithm for the Determination of the Polynomial of Best Minimax Approximation to a Function Defined on a Finite Point Set

where q(x) is any polynomial of degree less than or equM to n. Although the properties which determine p ( x ) uniquely are well known, we state them here for future reference. In what follows u = (u0, u l , • -, Un+l) will always denote a vector, the coordinates of which are points of S satisfying uo < u~ < . • < u~+~. We shall denote the class of such vectors by T. For u in T, consider the following equations:
Sucrose Ingestion Induces Rapid AMPA Receptor Trafficking

The mechanisms by which natural rewards such as sugar affect synaptic transmission and behavior are largely unexplored. Here, we investigate regulation of nucleus accumbens synapses by sucrose intake. Previous studies have shown that AMPA receptor (AMPAR) trafficking is a major mechanism for regulating synaptic strength, and that in vitro, trafficking of AMPARs containing the GluA1 subunit takes place by a two-step mechanism involving extrasynaptic and then synaptic receptor transport. We report that in rat, repeated daily ingestion of a 25% sucrose solution transiently elevated spontaneous locomotion and potentiated accumbens core synapses through incorporation of Ca2+-permeable AMPA receptors (CPARs), which are GluA1-containing, GluA2-lacking AMPARs. Electrophysiological, biochemical, and quantitative electron microscopy studies revealed that sucrose training (7 d) induced a stable (>24 h) intraspinous GluA1 population, and that in these rats a single sucrose stimulus rapidly (5 min) but transiently (<24 h) elevated GluA1 at extrasynaptic sites. CPARs and dopamine D1 receptors were required in vivo for elevated locomotion after sucrose ingestion. Significantly, a 7 d protocol of daily ingestion of a 3% solution of saccharin, a noncaloric sweetener, induced synaptic GluA1 similarly to 25% sucrose ingestion. These findings identify multistep GluA1 trafficking, previously described in vitro, as a mechanism for acute regulation of synaptic transmission in vivo by a natural orosensory reward. Trafficking is stimulated by a chemosensory pathway that is not dependent on the caloric value of sucrose.
Re-inventing the Asian model : the case of Singapore

This monograph written for the Institute of Policy Studies (Singapore) focuses on the structural weaknesses in the Singapore economy, in particular those which the author feels have been under-appreciated. Thus it pays special attention to the effect government intervention has had on the economy and finds that several unintended consequences of policy actions have accumulated over the years. Several of these have become serious constraints on Singapore's ability to adjust effectively to the rising challenges in the global and regional environments. With these aspects in mind, the monograph: analyses the nature of the challenges faced by the Singapore economy; assesses the structural weaknesses are which inhibit effective adjustment to address them, and seek out their root causes; makes recommendations as to specific policy changes that are necessary. The monograph asserts that Singapore will retain a sufficient critical mass of regional manufacturing and service activities to remain a dynamic growth center in the Asia-Pacific region, and that the impact of increasing competition, especially from China and Malaysia, has been exaggerated.
Branch penalty reduction on IBM Cell SPUs via software branch hinting

As power-efficiency becomes paramount concern in processor design, architectures are coming up that completely do away with hardware branch prediction, and rely solely on software branch hinting. A popular example is the Synergistic Processing Unit (SPU) in the IBM Cell processor. To be able to minimize the branch penalty using branch hint instructions, in addition to estimating the branch probabilities (which has been looked at before [6, 25, 24]), it is important to carefully insert branch hints. Towards this, in this paper, we i) construct a branch penalty model for compiler, ii) formulate the problem of minimizing branch penalty using branch hinting and iii) propose a heuristic to solve this problem. The heuristic is based on three basic techniques that we introduce in this paper: NOP padding, hint pipelining, and nested loop restructuring. Experimental results on several benchmarks show that our solution can reduce the branch penalty as much as 35.4% over the previous approach.
Epidemiological modeling of network worm infections and countermeasures

Fast spreading network worms continue to pose a threat to the Internet due to their virulence, speed and the continuous discovery of wormable vulnerabilities. Mathematical models for worm propagation can help us to understand the epidemiology of worm outbreaks and to devise effective defense mechanisms. In this paper, we report the epidemiological modeling and analysis of worm propagation and a distributed worm detection and prevention countermeasure. The work is based on the Slammer and Witty worm characteristics and employs the widely used Susceptible-Infected biological model. The epidemiological modeling shows that the SI model can be used to represent the virulence of random scanning worms and to quantify the effectiveness of worm countermeasures.
Movement Restrictions, Agricultural Trade and Price Transmission between Israel and the West Bank

Imposing military security measures as a consequence of violent conflict may lead to depressing economic effects for all parties involved. One implication is the limited ability to conduct trade, which in turn brings about welfare losses to the economic agents involved and may threat livelihoods and food security. This paper focuses on the consequences of the Israeli-Palestinian conflict, as a prominent example, on bilateral agricultural trade and price dynamics. For this purpose, we consider high-frequency wholesale price data and data on movement restrictions (complete closures) which were imposed by the Israeli Defense Forces in the West Bank between May 2007 and December 2008. In particular, we study the price dynamics of cucumbers and apples, two crops which play an important role for bilateral trade. The spatial and temporal price relationships are assessed using a cointegration framework. Specifically, we use a novel multivariate exogenous regime-switching vector error correction model and employ a recently developed extension of Johansen’s cointegration estimation method. We find the wholesale markets of cucumbers and apples in Hebron and Tel Aviv to be integrated. For both products, the price differentials between both markets quickly adjust to short run deviations from the long-run price equilibria. The regime-dependent model suggests that the movement restrictions effectively cut off both markets from each other temporarily.
Clinical course and prognosis in ulcerative colitis: results from population-based and observational studies

The clinical course of ulcerative colitis (UC) may range from a quiescent course with prolonged periods of remission to fulminant disease requiring intensive medical treatment or surgery. Disease outcome is often determined by relapse rates, the development of colorectal cancer (CRC) and mortality rates. Early patient classification, identifying those with a high risk of developing complicated disease, is essential for choosing appropriate treatment. This paper reviews the clinical outcomes of UC patients as reported in population-based and observational studies representative of the whole patient population. Extensive colitis, a high level of systemic symptoms and young age at diagnosis are factors associated with a high risk of colectomy. Patients with distal disease who progress to extensive colitis seem to be a subgroup with an especially high risk of colectomy. Some prognostic factors of severe disease have been identified which could be used to optimize treatment and possibly reduce future complications. The overall risk of CRC and mortality was not significantly different from that of the background population. These results may have implications for follow-up strategies, especially regarding endoscopic surveillance of UC patients.
The Neurosteroid Allopregnanolone Promotes Proliferation of Rodent and Human Neural Progenitor Cells and Regulates Cell-Cycle Gene and Protein Expression

Our previous research demonstrated that the neuroactive progesterone metabolite allopregnanolone (3α-hydroxy-5α-pregnan-20-one) rapidly induced hippocampal neuron neurite regression (Brinton, 1994). We hypothesized that allopregnanolone-induced neurite regression was a prelude to mitogenesis initiated by a rise in intracellular calcium. Supporting this hypothesis, the current data demonstrate that allopregnanolone, in a dose-dependent manner, induces a significant increase in proliferation of neuroprogenitor cells (NPCs) derived from the rat hippocampus and human neural stem cells (hNSCs) derived from the cerebral cortex. Proliferation was determined by incorporation of bromodeoxyuridine and [3H]thymidine, fluorescence-activated cell sorter analysis of murine leukemia virus-green fluorescent protein-labeled mitotic NPCs, and total cell number counting. Allopregnanolone-induced proliferation was isomer and steroid specific, in that the stereoisomer 3β-hydroxy-5β-pregnan-20-one and related steroids did not increase [3H]thymidine uptake. Immunofluorescent analyses for the NPC markers nestin and Tuj1 indicated that newly formed cells were of neuronal lineage. Furthermore, microarray analysis of cell-cycle genes and real-time reverse transcription-PCR and Western blot validation revealed that allopregnanolone increased the expression of genes that promote mitosis and inhibited the expression of genes that repress cell proliferation. Allopregnanolone-induced proliferation was antagonized by the voltage-gated L-type calcium channel (VGLCC) blocker nifedipine, consistent with the finding that allopregnanolone induces a rapid increase in intracellular calcium in hippocampal neurons via a GABA type A receptor-activated VGLCC (Son et al., 2002). These data demonstrate that allopregnanolone significantly increased rat NPC and hNSC proliferation with concomitant regulation in mitotic cell-cycle genes via a VGLCC mechanism. The therapeutic potential of allopregnanolone as a neurogenic molecule is discussed.
Autism and social disconnection in interpersonal rocking

Individuals with autism spectrum disorders (ASDs) have significant visuomotor processing deficits, atypical motoric behavior, and often substantial problems connecting socially. We suggest that the perceptual, attentional, and adaptive timing deficiencies associated with autism might directly impact the ability to become a socially connected unit with others. Using a rocking chair paradigm previously employed with typical adults, we demonstrate that typically-developing (TD) children exhibit spontaneous social rocking with their caregivers. In contrast, children diagnosed with ASD do not demonstrate a tendency to rock in a symmetrical state with their parents. We argue that the movement of our bodies is one of the fundamental ways by which we connect with our environment and, especially, ground ourselves in social environments. Deficiencies in perceiving and responding to the rhythms of the world may have serious consequences for the ability to become adequately embedded in a social context.
White Flight: Atlanta and the Making of Modern Conservatism

List of Illustrations ix Acknowledgments xi Introduction 3 CHAPTER ONE: "The City oo Busy to Hate": Atlanta and the Politics of Progress 19 CHAPTER TWO: From Radicalism to "Respectability": Race, Residence, and Segregationist Strategy 42 C HAPTER THREE: From Community to Individuality: Race, Residence, and Segregationist Ideology 78 CHAPTER FOUR: The Abandonment of Public Space: Desegregation, Privatization, and the ax Revolt 105 CHAPTER FIVE: The "Second Battle of Atlanta": Massive Resistance and the Divided Middle Class 131 CHAPTER SIX: The Fight for "Freedom of Association": School Desegregation and White Withdrawal 161 CHAPTER SEVEN: Collapse of the Coalition: Sit-Ins and the Business Rebellion 180 CHAPTER EIGHT: "The Law of the Land": Federal Intervention and the Civil Rights Act 205 CHAPTER NINE: City Limits: Urban Separatism and Suburban Secession 234 EPILOGUE: The Legacies of White Flight 259 List of Abbreviations 267 Notes 269 Index 313
Learning approach for classification of GENEActiv accelerometer data for unique activity identification

Recent popular emphasis on exercise for personal wellbeing has created a demand for techniques which monitor and classify human activities. Previous studies have shown promising results in applying various classification and feature extraction methods for identifying unique physical activities on various datasets. We apply learning techniques to GENEactiv accelerometer recordings to identify and monitor a wide range of daily activities. The dataset is composed of 92 participants, of ages 20-65, performing 25 unique activities, both ambulatory and non-ambulatory. The algorithm identified 130 different time and frequency domain features and selected the most efficient features with the sequential forward selection algorithm. With classification in two stages with both Gaussian mixture model (GMM) and hidden Markov model (HMM) we have combined the activities with similar features. We have also shown a comparative study between the two classifiers. We achieved an accuracy of 95.5% while classifying 10 unique activities with HMM and 89.7% while classifying 9. The most efficient result is obtained using HMM in 2-D feature space, where it is able to classify 15 unique activities at an accuracy of 90.12%.
Issues in applied statistics for public health bioterrorism surveillance using multiple data streams: research needs

The objective of this report is to provide a basis to inform decisions about priorities for developing statistical research initiatives in the field of public health surveillance for emerging threats. Rapid information system advances have created a vast opportunity of secondary data sources for information to enhance the situational and health status awareness of populations. While the field of medical informatics and initiatives to standardize healthcare‐seeking encounter records continue accelerating, it is necessary to adapt analytic and statistical methodologies to mature in sync with sibling information science technologies. One major right‐of‐passage for statistical inference is to advance the optimal application of analytic methodologies for using multiple data streams in detecting and characterizing public health population events of importance. This report first describes the problem in general and the data context, then delineates more specifically the practical nature of the problem and the related issues. Approaches currently applied to data with time‐series, statistical process control and traditional inference concepts are described with examples in the section on Statistics and the Role of the Analytic Surveillance Data Monitor. These are the techniques that are providing substance to surveillance professionals and enabling use of multiple data streams. The next section describes use of a more complex approach that takes temporal as well as spatial dimensions into consideration for detection and situational awareness regarding event distributions. The space–time statistic has successfully been used to detect and track public health events of interest. Important research questions which are summarized at the end of this report are described in more detail with respect to the methodological application in the respective sections. This was thought to help elucidate the research requirements as summarized later in the report. Following the description of the space–time scan statistical application; this report extends to a less traditional area of promise given what has been observed in recent application of analytic methods. Bayesian networks (BNs) represent a conceptual step with advantages of flexibility for the public health surveillance community. Progression from traditional to the more extending statistical concepts in the context of the dynamic status quo of responsibility and challenge, leads to a conclusion consisting of categorical research needs. The report is structured by design to inform judgment about how to build on practical systems to achieve better analytic outcomes for public health surveillance. There are references to research issues throughout the sections with a summarization at the end, which also includes items previously unmentioned in the report. Copyright © 2007 John Wiley & Sons, Ltd.
Development of an Active Power Reserve Management Method for DC Applied Wave-Wind Combined Generation Systems

A system that combines a wind turbine and a wave generator can share the off-shore platform and therefore mix the advantages of the transmission system construction and the power conversion system. The current hybrid generation system considers output limitation according to the instructions of the transmission system operator (TSO), and controls the profile using wind turbine pitch control. However, the integrated wave generation system utilizing a DC network does not adapt a power limitation scheme due to its mechanical constraints. In this paper, a control plan focusing on the electrical section of wave generators is formed in order to effectively manage the output profile of the hybrid generation system. The plan pays attention to power reserve flexibility for the utility grid using the analysis of the controllable elements. Comparison with the existing system is performed based on real offshore conditions. With the help of power system computer aided design (PSCAD) simulation, the ability of the novel technique is estimated by proposing the real power control based on the reference signal of TSO and the reactive power capacity it produces.
Effect of Nano-Silver on Growth of Saffron in Flooding Stress

Saffron (Crocus sativus) is cultivated as spices, medicinal and aromatic plant species. At autumn season, heavy rainfall can cause flooding stress and inhibits growth of saffron. Thus this research was conducted to study the effect of silver ion (as an ethylene inhibitor) on growth of saffron under flooding conditions. The corms of saffron were soaked with one concentration of nano silver (0, 40, 80 or 120 ppm) and then planting under flooding stress or non flooding stress conditions. Results showed that number of roots, root length, root fresh and dry weight, leaves fresh and dry weight were reduced by 10 day flooding stress. Soaking saffron corms with 40 or 80 ppm concentration of nano silver rewarded the effect of flooding stress on the root number, by increasing it. Furthermore, 40 ppm of nano silver increased root length in stress. Nano silver 80 ppm in flooding stress, increased leaves dry weight. Keywords—Flooding stress, Nano-silver, Saffron.
An approach for training subspace distribution clustering HMM

In this paper, a new approach to train subspace distribution clustering HMM (SDCHMM) is described. With the multi-correlation coefficient and the Bhattacharyya distance, this approach is used for dividing the acoustical observation vector space, clustering subspace Gaussian distribution and getting subspace Gaussian prototypes. To evaluate the performance of the SDCHMM recognizer, a series of speaker-independent experiments are run to recognize Chinese digits. In comparison to a continuous density HMM (CDHMM) recognizer, a SDCHMM recognizer achieves 2- to 10-fold reduction in parameters requirement for acoustic models, and runs 20% - 25% faster without any loss of recognition accuracy.
A PERSONAL VEHICLE TRANSACTIONS CHOICE MODEL FOR USE IN FORECASTING DEMAND FOR FUTURE ALTERNATIVE-FUEL VEHICLES

A discrete choice model has been developed in which the choice alternatives consist of vehicle transactions rather than portfolios of vehicle holdings. The model is based on responses to customized stated preference questions involving both hypothetical future vehicles and the household`s current vehicle holdings. The stated choices were collected from 4747 survey respondents located throughout most of the urbanized portions of California. Respondents were asked what their next vehicle transaction would most likely be (replace a current vehicle, add another vehicle, or dispose of a current vehicle), and respondents who wanted to replace or add vehicles were asked to indicate their most preferred vehicle from a set of six hypothetical vehicles. The hypothetical vehicles were described in terms of fourteen attributes, manipulated according to an experimental design. The transactions model is a multinomial logic model of the choice of the hypothetical vehicles and whether or not the hypothetical vehicle will be a replacement or addition to the household fleet. The model is conditioned on the household`s current vehicle stock, and the characteristics of the current vehicles are important explanators of the stated preference choices. In addition to the model estimates, forecasts are given for a base case scenario in 1998.more » The model is one component in a micro-simulation demand forecasting system being designed to produce annual forecasts of new and used vehicle demand by type of vehicle and geographic area. The system will also forecast annual vehicle miles traveled for all vehicles and recharging demand by time of day for electric vehicles. These results are potentially useful to utility companies in their demand-side management planning, to public agencies in their evaluation incentive schemes, and to manufacturers faced with designing and marketing alternative-fuel vehicles. « less