Miracle-dz/UniFAR-FTUs huggingface dataset:
IS US REAL GNP CHAOTIC ? ON USING THE BDS TEST TO DECIDE WHETHER AN ARMA MODEL FOR THE US GNP GENERATES

In this paper we use the BDS test developed by Brock-Dechert-Scheinkman(1987) to investigate whether ARIMA models for the US real GNP generate i.i. d. residuals. The second step, after reviewing some results from Brock-Sayers(1988) and Scheinkman-LeBaron(1989), SL, we will use a different kind of specifications for the US real GNP such as a model with different volatility pre and post World War II (WWII), as in SL(1989), and a threshold autoregressive specification as in Potter(1990). The last point consists of analysing a modified threshold model that takes into account the observation made by SL(1989) and next we evaluate the forecast performance of the " best " models among those examined.
Optimal linear and cyclic locally repairable codes over small fields

We consider locally repairable codes over small fields and propose constructions of optimal cyclic and linear codes in terms of the dimension for a given distance and length. Four new constructions of optimal linear codes over small fields with locality properties are developed. The first two approaches give binary cyclic codes with locality two. While the first construction has availability one, the second binary code is characterized by multiple available repair sets based on a binary Simplex code. The third approach extends the first one to q-ary cyclic codes including (binary) extension fields, where the locality property is determined by the properties of a shortened first-order Reed- Muller code. Non-cyclic optimal binary linear codes with locality greater than two are obtained by the fourth construction.
A numerical study of transport and shot noise in 2D hopping

We have used modern supercomputer facilities to carry out extensive Monte Carlo simulations of 2D hopping (at negligible Coulomb interaction) in conductors with a completely random distribution of localized sites in both space and energy, within a broad range of the applied electric field E and temperature T, both within and beyond the variable-range hopping region. The calculated properties include not only dc current and statistics of localized site occupation and hop lengths, but also the current fluctuation spectrum. Within the calculation accuracy, the model does not exhibit 1/f noise, so that the low-frequency noise at low temperatures may be characterized by the Fano factor F. For sufficiently large samples, F scales with conductor length L as (Lc/L)α, where α = 0.76 ± 0.08<1, and parameter Lc is interpreted as the average percolation cluster length. At relatively low E, the electric field dependence of parameter Lc is compatible with the law which follows from directed percolation theory arguments.
Estimation of Clusters Number and Initial Centers of K-Means Algorithm Using Watershed Method

In K-means clustering algorithm, the selection of cluster number k and initial K-means center has certain influence on the result. It would generate very different aggregation result when confronting with some certain types of data set. This paper aims at proposing an estimation method to evaluate the initial parameters for K-means algorithm. The estimation is executed through data analysis, which contains two main steps: the data would be transformed into data dimensional density first, and then, watershed method would be applied to divide the data space into multiple regions. Each regional center is selected as an initial K-means center, and the number of region is set as cluster number. This estimation method takes advantage of image segmentation ideology and the case study in this paper showed its favorable performance.
Sildenafil Effects on Exercise, Neurohormonal Activation, and Erectile Dysfunction in Congestive Heart Failure: A Double-Blind, Placebo-Controlled, Randomized Study Followed by a Prospective Treatment for Erectile Dysfunction

Background—Erectile dysfunction (ED) is common in patients with congestive heart failure (CHF). ED reduces quality of life, and it may affect compliance, thereby impairing the success of CHF treatment. Methods and Results—In the first phase (fixed-dose double-blind, randomized, placebo-controlled, two-way crossover study), we studied in 23 men with CHF the effects of 50 mg sildenafil on exercise and neurohormonal activation. Patients underwent a treadmill 6-minute cardiopulmonary walking (6′WT) test followed by a maximal cardiopulmonary exercise test (ET). In the second phase, patients received sildenafil, taken as required for ED. Sildenafil reduced the heart rate (HR) (bpm) before the 6′WT (from 75±15 to 71±14, P =0.02) and ET (from 75±15 to 71±15, P =0.02); the systolic blood pressure (mm Hg) before the 6′WT (from 116±18 to 108±18, P =0.004) and ET (from 116±15 to 108±17, P =0.001); the diastolic blood pressure before the 6′WT (from 69±9 to 63±11, P =0.01) and ET (from 70±8 to 65±10, P =0.004); and the Ve/Vco2 slope during the 6′WT (from 32±7 to 31±6, P =0.04) and ET (from 33±8 to 31±5, P =0.03). Sildenafil attenuated the HR increment during the 6′WT (P =0.003) and ET (P =0.000). Sildenafil increased the peak ˙ o2 from 16.6±3.4 to 17.7±3.4 mL/kg per min (P =0.025) and the exercise time from 12.3±3.4 to 13.7±3.2 minutes (P =0.003). Sildenafil improved most scores of International Index of Erectile Function. Conclusions—Sildenafil was tolerated and effective for ED treatment in CHF, and improved the exercise capacity. The reduction of HR during exercise with sildenafil could theoretically decrease the myocardial oxygen consumption during sexual activity.
Context-Dependent Classes in a Hybrid Recurrent Network-HMM Speech Recognition System

A method for incorporating context-dependent phone classes in a connectionist-HMM hybrid speech recognition system is introduced. A modular approach is adopted, where single-layer networks discriminate between different context classes given the phone class and the acoustic data. The context networks are combined with a context-independent (CI) network to generate context-dependent (CD) phone probability estimates. Experiments show an average reduction in word error rate of 16% and 13% from the CI system on ARPA 5,000 word and SQALE 20,000 word tasks respectively. Due to improved modelling, the decoding speed of the CD system is more than twice as fast as the CI system.
Accounting for free-surface multiples in Marchenko imaging

Imagine placing a receiver at any location in the earth and recording the response at that location to sources on the surface. In such a world, we could place receivers around our reservoir to better image the reservoir and understand its properties. Realistically, this is not a feasible approach for understanding the subsurface. We have developed an alternative and realizable approach to obtain the response of a buried virtual receiver for sources at the surface. Our method is capable of retrieving the Green’s function for a virtual point in the subsurface to the acquisition surface. In our case, a physical receiver is not required at the subsurface point; instead, we require the reflection measurements for sources and receivers at the surface of the earth and a macromodel of the velocity (no small-scale details of the model are necessary). We can interpret the retrieved Green’s function as the response to sources at the surface for a virtual receiver in the subsurface. We obtain this Green’s function by solving the Marchenko equation, an integral equation pertinent to inverse scattering problems. Our derivation of the Marchenko equation for the Green’s function retrieval takes into account the free-surface reflections present in the reflection response (previous work considered a response without free-surface multiples). We decompose the Marchenko equation into up- and downgoing fields and solve for these fields iteratively. The retrieved Green’s function not only includes primaries and internal multiples as do previous methods, but it also includes freesurface multiples. We use these up- and downgoing fields to obtain a 2D image of our area of interest, in this case, below a synclinal structure.
Emotional Well-Being and the Importance for Women with Fear of Birth to have a Known Midwife at Birth

Background: Previous research has shown that women with fear of childbirth often suffer from other mental health issues. Continuity of caregiver through a known midwife is best practice for pregnant women, and women with childbirth related fear value continuity of care. In Sweden the maternity care is fragmented and women’s opinion remains under-investigated. Objective: The aim of this study was to investigate emotional well-being and the importance of having a known midwife during birth in women referred to counselling for childbirth related fear. Design: Cross sectional study Setting: 3 Swedish hospitals providing counseling for childbirth related fear. Participants: Women who were referred for counseling due to fear of childbirth. Measures: The importance of having a known midwife at birth, background factors, emotional well-being and attitudes. Results: 77 women referred to counseling consented to participate. The majority of women were likely to present with previous or ongoing emotional distress, high levels of anxiety or depressive symptoms, low Sense of Coherence and Major worries. For the majority of women (71%) it was important to have a known midwife at birth and most important for women with high levels of childbirth fear. Conclusion: This study highlights that women referred to counseling due to fear of childbirth might need additional support to cope with their emotional distress. The results also indicated that having a known midwife at birth was important to these women, especially for women with higher fear. The option of having a known midwife during birth is rarely accomplished in Sweden due to the fragmentation of care.
A Unified Probabilistic Approach for Semantic Clustering of Relational Phrases

The task of finding synonymous relational phrases is important in natural language understanding problems such as question answering and paraphrase detection. While this task has been addressed by many previous systems, each of these existing approaches is limited either in expressivity or in scalability. To address this challenge, we present a large-scale statistical relational method for clustering relational phrases using Probabilistic Soft Logic (PSL) [1]. To assess the quality of our approach, we evaluated it relative to a set of baseline methods. The proposed technique was found to outperform the baselines for both clustering and link prediction, and was shown to be scalable enough to be applied to 200,000 relational phrases.
The Shifts of Diazotrophic Communities in Spring and Summer Associated with Coral Galaxea astreata, Pavona decussata, and Porites lutea

The coral holobiont often resides in oligotrophic waters; both coral cells and their symbiotic dinoflagellates possess ammonium assimilation enzymes and potentially benefit from the nitrogen fixation of coral-associated diazotrophs. However, the seasonal dynamics of coral-associated diazotrophs are not well characterized. Here, the seasonal variations of diazotrophic communities associated with three corals, Galaxea astreata, Pavona decussata, and Porites lutea, were studied using nifH gene amplicon pyrosequencing techniques. Our results revealed a great diversity of coral-associated diazotrophs. nifH sequences related to Alphaproteobacteria, Deltaproteobacteria, and Gammaproteobacteria were ubiquitous and dominant in all corals in two seasons. In contrast with the coral P. decussata, both G. astreata and P. lutea showed significant seasonal changes in the diazotrophic communities and nifH gene abundance. Variable diazotroph groups accounted for a range from 11 to 49% within individual coral samples. Most of the variable diazotrophic groups from P. decussata were species-specific, however, the majority of overlapping variable groups in G. astreata and P. lutea showed the same seasonal variation characteristics. Rhodopseudomonas palustris- and Gluconacetobacter diazotrophicus-affiliated sequences were relatively abundant in the summer, whereas a nifH sequence related to Halorhodospira halophila was relatively abundant in spring G. astreata and P. lutea. The seasonal variations of all diazotrophic communities were significantly correlated with the seasonal shifts of ammonium and nitrate, suggesting that diazotrophs play an important role in the nitrogen cycle of the coral holobiont.
Channel estimation based on Non-Equally Spaced Pilot allocation in OFDM system

This paper proposes the modifications in the Least Square (LS) estimator for the Orthogonal Frequency Division Multiplexing (OFDM) over fast fading Rayleigh channels in the presence of the Additive White Gaussian Noise (AWGN) to optimize its performance. The LS estimation has an inherent channel noise that degrades its performance. In our work, modifications in the LS estimator were proposed to reduce the inherent noise and interpolation error. The channel energy has the concentrated nature in time domain. The first set of taps containing almost all of channel energy for the sample spaced channel was considered. The performance analysis of the modified LS (M-LS) estimator was made both for comb-type and Non-Equally Spaced Pilots (NSP). Simulation results revealed the performance improvement of the M-LS estimator with both comb-type pilot arrangement and NSP over conventional LS estimator with one-dimensional interpolation techniques for comb-type pilot arrangement. A M-LS estimator has optimum performance for linearly spaced pilots compared to NSP.
Explore Chinese Encyclopedic Knowledge to Disambiguate Person Names

This paper presents the HITSZ-PolyU system in the CIPS-SIGHAN bakeoff 2012 Task 3, Chinese Personal Name Disambiguation. This system leveraged the Chinese encyclopedia Baidu Baike (Baike) as the external knowledge to disambiguate the person names. Three kinds of features are extracted from Baike. They are the entities’ texts in Baike, the entities’ work-of-art words and titles in the Baike. With these features, a Decision Tree (DT) based classifier is trained to link test names to nodes in the NameKB. Besides, the contextual information surrounding test names is used to verify whether test names are person name or not. Finally, a simple clustering approach is used to group NIL test names that have no links to the NameKB. Our proposed system attains 64.04% precision, 70.1% recall and 66.95% F-score.
Large Deviations: Advanced Probability for Undergrads

In the branch of probability called “large deviations,” rates of convergence (e.g. of the sample mean) are considered. The theory makes use of the moment generating function. So, particularly for sums of independent and identically distributed random variables, the theory can be made accessible to senior undergraduates after a first course in stochastic processes. This paper describes a directed independent study in large deviations offered to a strong senior, providing a sample outline and discussion of resources. Learning points are also highlighted.
Ultrabroadband coherent supercontinuum frequency comb

We present detailed studies of the coherence properties of an ultrabroadband supercontinuum, enabled by a comprehensive approach involving continuous-wave laser sources to independently probe both the amplitude and phase noise quadratures across the entire spectrum. The continuum coherently spans more than 1.5 octaves, supporting Hz-level comparison of ultrastable lasers at 698 nm and 1.54 {mu}m. We present a complete numerical simulation of the accumulated comb coherence in the limit of many pulses, in contrast to the single-pulse level, with systematic experimental verification. The experiment and numerical simulations reveal the presence of quantum-seeded broadband amplitude noise without phase coherence degradation, including the discovery of a dependence of the supercontinuum coherence on the fiber fractional Raman gain.
Semidefinite and Second Order Cone Programming Seminar Fall 2012 Project : Robust Optimization and its Application of Robust Portfolio Optimization Instructor :

There are several different methods to treat uncertainty in literacy. First, sensitivity analysis which is a post-optimization method analyzing stability of generated solutions. Second, stochastic programming is a modeling approach, and this method is limited to that the uncertainty is stochastic in nature. Third, “Robust Mathematical Programming” is that a candidate solutions allowing to violate the “scenario realizations” of the constraints instead of considering fixed “nominal” data for several scenarios considered, and add penalty terms in the objective function. [2] The robust optimization is a method to handle deterministic uncertainty in optimization problems [4]. Majority of uncertain data are due to prediction errors, measurement errors, and implementation errors. Moreover, small errors in data values can make optimal solutions highly infeasible, and the robust optimization prevent the infeasible solutions. This paper first summarizes the basic concept of robust optimization [1] and shows its application of robust portfolio optimization.
Sequence-Based Polymorphisms in the Mitochondrial D-Loop and Potential SNP Predictors for Chronic Dialysis

Background The mitochondrial (mt) displacement loop (D-loop) is known to accumulate structural alterations and mutations. The aim of this study was to investigate the prevalence of single nucleotide polymorphisms (SNPs) within the D-loop among chronic dialysis patients and healthy controls. Methodology and Principal Findings We enrolled 193 chronic dialysis patients and 704 healthy controls. SNPs were identified by large scale D-loop sequencing and bioinformatic analysis. Chronic dialysis patients had lower body mass index, blood thiols, and cholesterol levels than controls. A total of 77 SNPs matched with the positions in reference of the Revised Cambridge Reference Sequence (CRS) were found in the study population. Chronic dialysis patients had a significantly higher incidence of 9 SNPs compared to controls. These include SNP5 (16108Y), SNP17 (16172Y), SNP21 (16223Y), SNP34 (16274R), SNP35 (16278Y), SNP55 (16463R), SNP56 (16519Y), SNP64 (185R), and SNP65 (189R) in D-loop of CRS. Among these SNPs with genotypes, SNP55-G, SNP56-C, and SNP64-A were 4.78, 1.47, and 5.15 times more frequent in dialysis patients compared to controls (P<0.05), respectively. When adjusting the covariates of demographics and comorbidities, SNP64-A was 5.13 times more frequent in dialysis patients compared to controls (P<0.01). Furthermore, SNP64-A was found to be 35.80, 3.48, 4.69, 5,55, and 4.67 times higher in female patients and in patients without diabetes, coronary artery disease, smoking, and hypertension in an independent significance manner (P<0.05), respectively. In patients older than 50 years or with hypertension, SNP34-A and SNP17-C were found to be 7.97 and 3.71 times more frequent (P<0.05) compared to patients younger than 50 years or those without hypertension, respectively. Conclusions and Significance The results of large-scale sequencing suggest that specific SNPs in the mtDNA D-loop are significantly associated with chronic dialysis. These SNPs can be considered as potential predictors for chronic dialysis.
Efficient and effective ranking in Top-k exploration for keyword search on RDF

Ranking solutions is an important issue in Information Retrieval because it greatly influences the quality of results. In this context, keyword based search approaches use to consider solutions sorting as least step of the overall process. Ranking and building solutions are completely separate steps running autonomously. This may penalize the retrieving information process because it binds to order all found matching elements including (possible) irrelevant information. In this paper we present a theoretical study of YAANII, a novel technique to keyword based search over semantic data. We demonstrate how effectiveness of the answers depends not so much on the quality of the scoring metrics but on the way such criteria are involved.
Searching for the Perfect Wave: The Effect of Radiofrequency Electromagnetic Fields on Cells

There is a growing concern in the population about the effects that environmental exposure to any source of “uncontrolled” radiation may have on public health. Anxiety arises from the controversial knowledge about the effect of electromagnetic field (EMF) exposure to cells and organisms but most of all concerning the possible causal relation to human diseases. Here we reviewed those in vitro and in vivo and epidemiological works that gave a new insight about the effect of radio frequency (RF) exposure, relating to intracellular molecular pathways that lead to biological and functional outcomes. It appears that a thorough application of standardized protocols is the key to reliable data acquisition and interpretation that could contribute a clearer picture for scientists and lay public. Moreover, specific tuning of experimental and clinical RF exposure might lead to beneficial health effects.
Volvelles, domes and wristbands: embedding digital fabrication within a visitor's trajectory of engagement

We present the findings of an empirical design study exploring how situating digital fabrication within a souvenir-making activity can enrich an audience's encounter with cultural events and engage visitors in discussion and reflection upon their experiences. During an incremental accumulative design process, in collaboration with an arts organisation, we developed a series of fabrication activities that offered visitors the opportunity to create their own personalised souvenirs based on their experience of a cultural event. By analyzing visitors' trajectories of engagement with the event we explore three key findings: activity embedded digital fabrication engages new audiences, encourages conversation and reflection, and presents organisations with new and more playful ways to gain insights into audience experiences.
Calibration of an interrupted traffic flow system using NGSIM trajectory data sets

This paper calibrates an interrupted traffic flow system model using the trajectory datasets provided by Next Generation SIMulation (NGSIM) program. The realistic lane changing may cut off the traffic flow into discontinuous flow, giving rise to congestion and vehicle delay. The aim of this paper is to study the car-following behaviors of drivers in real traffic scenes in which lane changing happens. The interrupted traffic flow system model is calibrated by minimizing the deviations between the observed dynamics and the simulated trajectory with a nonlinear optimization procedure-Levenberg-Marquardt Algorithm. The reliability and robustness of the nonlinear fits are assessed for the deviation from one trajectory, acceleration and deceleration process respectively. The required errors are 0.0172 and 0.2845, which are sameness to representative one obtained in previous studies. Therefore, a used widely model that reflects the lane changing situation in reality is achieved.