Miracle-dz/UniFAR-FTUs huggingface dataset:
An optimal algorithm for the all-nearest-neighbors problem

Given a set V of n points in k-dimensional space, and an Lq-metric (Minkowski metric), the All-Nearest-Neighbors problem is defined as follows: For each point p in V, find all those points in V-{p} that are closest to p under the distance metric Lq. We give an O(nlogn) algorithm for the All-Nearest-Neighbors problem, for fixed dimension k and fixed metric Lq. Since there is an Ω(n logn) lower bound, in the algebraic decision tree model of computation, on the time complexity of any algorithm that solves the All-Nearest-Neighbors problem (for k = 1), the running time of our algorithm is optimal upto a constant.
Pronouncing Text by Analogy

Pronunciation-by-analogy (PbA) is an emerging technique for text-phoneme conversion based on a psychological model of reading aloud. This paper explores the impact of certain basic implementational choices on the performance of various PbA models. These have been tested on their ability to pronounce sets of short pseudowords previously used in similar studies, as well as lexical words temporarily removed from the dictionary. Best results of 85.7% and 67.9% words correct are obtained for the pseudowords and lexical words respectively, casting doubt on certain previous-reported performance figures in the literature.
Modeling vanet deployment in urban settings

The growing interest in wireless Vehicular Ad Hoc Networks (VANETs) has prompted greater research into simulation models that better reflect urban VANET deployments. Still, we lack a systematic understanding of the required level of simulation details in modeling various real-world urban constraints. In this work, we developed a series of simulation models that account for street layout, traffic rules, multilane roads, acceleration-deceleration, and RF attenuation due to obstacles. Using real and controlled synthetic maps, we evaluated the sensitivity of the simulation results toward these details. Our results indicate that the delivery ratio and packet delays in VANETs are more sensitive to the clustering effect of vehicles at intersections and their acceleration/deceleration. The VANET performance appears to be only marginally affected by the simulation of multiple lanes and careful synchronization at traffic signals. We also found that the performance in dense VANETs improves significantly when routing decisions are limited to a wireless backbone of mesh nodes, whereas in sparse VANETs, performance improves when vehicles also participate in ad hoc routing. Finally, through measurement and analysis of signal strengths around urban city blocks, we show that the effect of signal attenuation due to physical obstacles can potentially be parameterized in simulations. Our work provides a starting point for further understanding and development of more accurate VANET simulation model.
Analyzing the Factors Influencing Exclusive Breastfeeding Using the Generalized Poisson Regression Model

Exclusive breastfeeding is the feeding of a baby on no other milk apart from breast milk. Exclusive breastfeeding during the first 6 months of life is of fundamental importance because it supports optimal growth and development during infancy and reduces the risk of obliterating diseases and problems. Moreover, in developed countries, exclusive breastfeeding has decreased the incidence and/or severity of diarrhea, lower respiratory infection and urinary tract infection. In this paper, we study the factors that influence exclusive breastfeeding and use the Generalized Poisson regression model to analyze the practices of exclusive breastfeeding in Mauritius. We develop two sets of quasi-likelihood equations (QLE)to estimate the parameters. Keywords—Exclusive breastfeeding, Regression model, Quasilikelihood.
Robust Locally-Linear Controllable Embedding

Embed-to-control (E2C) is a model for solving high-dimensional optimal control problems by combining variational auto-encoders with locally-optimal controllers. However, the E2C model suffers from two major drawbacks: 1) its objective function does not correspond to the likelihood of the data sequence and 2) the variational encoder used for embedding typically has large variational approximation error, especially when there is noise in the system dynamics. In this paper, we present a new model for learning robust locally-linear controllable embedding (RCE). Our model directly estimates the predictive conditional density of the future observation given the current one, while introducing the bottleneck between the current and future observations. Although the bottleneck provides a natural embedding candidate for control, our RCE model introduces additional specific structures in the generative graphical model so that the model dynamics can be robustly linearized. We also propose a principled variational approximation of the embedding posterior that takes the future observation into account, and thus, makes the variational approximation more robust against the noise. Experimental results show that RCE outperforms the E2C model, and does so significantly when the underlying dynamics is noisy.
The magnetic navigation system allows safety and high efficacy for ablation of arrhythmias

Aims We aimed to evaluate the safety and long-term efficacy of the magnetic navigation system (MNS) in a large number of patients. The MNS has the potential for improving safety and efficacy based on atraumatic catheter design and superior navigation capabilities. Methods and results In this study, 610 consecutive patients underwent ablation. Patients were divided into two age- and sex-matched groups. Ablations were performed either using MNS (group MNS, 292) or conventional manual ablation [group manual navigation (MAN), 318]. The following parameters were analysed: acute success rate, fluoroscopy time, procedure time, complications [major: pericardial tamponade, permanent atrioventricular (AV) block, major bleeding, and death; minor: minor bleeding and temporary AV block]. Recurrence rate was assessed during follow-up (15 ± 9.5 months). Subgroup analysis was performed for the following groups: atrial fibrillation, isthmus dependent and atypical atrial flutter, atrial tachycardia, AV nodal re-entrant tachycardia, circus movement tachycardia, and ventricular tachycardia (VT). Magnetic navigation system was associated with less major complications (0.34 vs. 3.2%, P = 0.01). The total numbers of complications were lower in group MNS (4.5 vs. 10%, P = 0.005). Magnetic navigation system was equally effective as MAN in acute success rate for overall groups (92 vs. 94%, P = ns). Magnetic navigation system was more successful for VTs (93 vs. 72%, P < 0.05). Less fluoroscopy was used in group MNS (30 ± 20 vs. 35 ± 25 min, P < 0.01). There were no differences in procedure times and recurrence rates for the overall groups (168 ± 67 vs. 159 ± 75 min, P = ns; 14 vs. 11%, P = ns; respectively). Conclusions Our data suggest that the use of MNS improves safety without compromising efficiency of ablations. Magnetic navigation system is more effective than manual ablation for VTs.
Divergence of human and mouse brain transcriptome highlights Alzheimer disease pathways

Because mouse models play a crucial role in biomedical research related to the human nervous system, understanding the similarities and differences between mouse and human brain is of fundamental importance. Studies comparing transcription in human and mouse have come to varied conclusions, in part because of their relatively small sample sizes or underpowered methodologies. To better characterize gene expression differences between mouse and human, we took a systems-biology approach by using weighted gene coexpression network analysis on more than 1,000 microarrays from brain. We find that global network properties of the brain transcriptome are highly preserved between species. Furthermore, all modules of highly coexpressed genes identified in mouse were identified in human, with those related to conserved cellular functions showing the strongest between-species preservation. Modules corresponding to glial and neuronal cells were sufficiently preserved between mouse and human to permit identification of cross species cell-class marker genes. We also identify several robust human-specific modules, including one strongly correlated with measures of Alzheimer disease progression across multiple data sets, whose hubs are poorly-characterized genes likely involved in Alzheimer disease. We present multiple lines of evidence suggesting links between neurodegenerative disease and glial cell types in human, including human-specific correlation of presenilin-1 with oligodendrocyte markers, and significant enrichment for known neurodegenerative disease genes in microglial modules. Together, this work identifies convergent and divergent pathways in mouse and human, and provides a systematic framework that will be useful for understanding the applicability of mouse models for human brain disorders.
An approximation algorithm for counting contingency tables

We present a randomized approximation algorithm for counting contingency tables, m × n non‐negative integer matrices with given row sums R = (r1,…,rm) and column sums C = (c1,…,cn). We define smooth margins (R,C) in terms of the typical table and prove that for such margins the algorithm has quasi‐polynomial NO(ln N) complexity, where N = r1 + … + rm = c1 + … + cn. Various classes of margins are smooth, e.g., when m = O(n), n = O(m) and the ratios between the largest and the smallest row sums as well as between the largest and the smallest column sums are strictly smaller than the golden ratio (1 + $ {\sqrt{5}} $)/2 ≈︁ 1.618. The algorithm builds on Monte Carlo integration and sampling algorithms for log‐concave densities, the matrix scaling algorithm, the permanent approximation algorithm, and an integral representation for the number of contingency tables. © 2010 Wiley Periodicals, Inc. Random Struct. Alg. , 2010
Electromagnetic fields as structure-function zeitgebers in biological systems: environmental orchestrations of morphogenesis and consciousness

Within a cell system structure dictates function. Any interaction between cells, or a cell and its environment, has the potential to have long term implications on the function of a given cell and emerging cell aggregates. The structure and function of cells are continuously subjected to modification by electrical and chemical stimuli. However, biological systems are also subjected to an ever-present influence: the electromagnetic (EM) environment. Biological systems have the potential to be influenced by subtle energies which are exchanged at atomic and subatomic scales as EM phenomena. These energy exchanges have the potential to manifest at higher orders of discourse and affect the output (behavior) of a biological system. Here we describe theoretical and experimental evidence of EM influence on cells and the integration of whole systems. Even weak interactions between EM energies and biological systems display the potential to affect a developing system. We suggest the growing literature of EM effects on biological systems has significant implications to the cell and its functional aggregates.
Trifolium pratense and T. repens (Leguminosae): Edible Flower Extracts as Functional Ingredients

Trifolium pratense (red clover) and T. repens (white clover) edible flowers were investigated for their chemical profile and health properties. The total phenols and flavonoids contents were evaluated. Quercetin, kaempferol, luteolin, rutin, and myricetin were used as markers and quantified by HPLC. The antioxidant effects were investigated by using different in vitro assays. Moreover, α-amylase, α-glucosidase and lipase inhibitory activities were evaluated. T. repens flowers extract showed a good radical scavenging activity in both DPPH and ABTS tests with IC50 values of 10.3 and 21.4 μg/mL, respectively. White clover extract demonstrated promising α-amylase and lipase inhibitory activities with IC50 values of 25.0 and 1.3 μg/mL, respectively. The obtained results support the use of Trifolium flowers as healthy food ingredients.
Learning to “Read Between the Lines” using Bayesian Logic Programs

Most information extraction (IE) systems identify facts that are explicitly stated in text. However, in natural language, some facts are implicit, and identifying them requires "reading between the lines". Human readers naturally use common sense knowledge to infer such implicit information from the explicitly stated facts. We propose an approach that uses Bayesian Logic Programs (BLPs), a statistical relational model combining firstorder logic and Bayesian networks, to infer additional implicit information from extracted facts. It involves learning uncertain common-sense knowledge (in the form of probabilistic first-order rules) from natural language text by mining a large corpus of automatically extracted facts. These rules are then used to derive additional facts from extracted information using BLP inference. Experimental evaluation on a benchmark data set for machine reading demonstrates the efficacy of our approach.
Potential Geographic Distribution of Hantavirus Reservoirs in Brazil

Hantavirus cardiopulmonary syndrome is an emerging zoonosis in Brazil. Human infections occur via inhalation of aerosolized viral particles from excreta of infected wild rodents. Necromys lasiurus and Oligoryzomys nigripes appear to be the main reservoirs of hantavirus in the Atlantic Forest and Cerrado biomes. We estimated and compared ecological niches of the two rodent species, and analyzed environmental factors influencing their occurrence, to understand the geography of hantavirus transmission. N. lasiurus showed a wide potential distribution in Brazil, in the Cerrado, Caatinga, and Atlantic Forest biomes. Highest climate suitability for O. nigripes was observed along the Brazilian Atlantic coast. Maximum temperature in the warmest months and annual precipitation were the variables that most influence the distributions of N. lasiurus and O. nigripes, respectively. Models based on occurrences of infected rodents estimated a broader area of risk for hantavirus transmission in southeastern and southern Brazil, coinciding with the distribution of human cases of hantavirus cardiopulmonary syndrome. We found no demonstrable environmental differences among occurrence sites for the rodents and for human cases of hantavirus. However, areas of northern and northeastern Brazil are also apparently suitable for the two species, without broad coincidence with human cases. Modeling of niches and distributions of rodent reservoirs indicates potential for transmission of hantavirus across virtually all of Brazil outside the Amazon Basin.
Frame level likelihood normalization for text-independent speaker identification using Gaussian mixture models

Proposes a new speaker identification system, where the likelihood normalization technique, which is widely used for speaker verification, is introduced. In the new system, which is based on Gaussian mixture models, every frame of the test utterance is input to all the reference models in parallel. In this procedure, for each frame, likelihoods from all the models are available, and hence they can be normalized at every frame. A special kind of likelihood normalization, called the 'weighting models rank', is also proposed. Experiments were performed using two databases-TIMIT and NTT. Evaluation results clearly show that the frame-level likelihood normalization technique is superior to the standard accumulated likelihood approach.
The validity of heart failure diagnoses obtained from administrative registers

Background: Population-based administrative registers could be used for identifying heart failure (HF) cases. However, the validity of the classification obtained from administrative registers is not known. Design: The validity of HF diagnoses obtained by record linkage of administrative databases in Finland was assessed against classification by three independent physicians. Methods: Data from the nationwide registers in Finland – the Hospital Discharge Register, Causes of Death Register, Drug Reimbursement Register, and pharmacy prescription data – were linked with the FINRISK 1997 survey data. Cases with hospitalizations before the survey date with HF as one of the discharge diagnoses, cases with special reimbursement for HF drugs before the survey date and cases with the use of furosemide before the survey date were classified as HF in the registers. All these cases, cases with baseline brain natriuretic peptide >100 pg/ml, and cases with use of digoxin were independently assessed by two physicians as HF/no HF. Discrepant cases were solved by a third physician. This classification was considered as the gold standard, against which the registers were assessed. Results: The specificity of the registers was 99.7% (95% CI 99.5–99.8%), positive predictive value 85.9% (95% CI 79.7–90.5%), negative predictive value 97.9% (95% CI 97.6–98.2%), and sensitivity 48.5% (95% CI 42.9–54.2%). Conclusions: Classification obtained from administrative registers has high specificity and can be used in follow-up studies with HF as an end point. Sensitivity is modest and administrative data should be used with caution for surveillance.
Face recognition based on nonsubsampled contourlet transform and block-based kernel Fisher linear discriminant

Face representation, including both feature extraction and feature selection, is the key issue for a successful face recognition system. In this paper, we propose a novel face representation scheme based on nonsubsampled contourlet transform (NSCT) and block-based kernel Fisher linear discriminant (BKFLD). NSCT is a newly developed multiresolution analysis tool and has the ability to extract both intrinsic geometrical structure and directional information in images, which implies its discriminative potential for effective feature extraction of face images. By encoding the the NSCT coefficient images with the local binary pattern (LBP) operator, we could obtain a robust feature set. Furthermore, kernel Fisher linear discriminant is introduced to select the most discriminative feature sets, and the block-based scheme is incorporated to address the small sample size problem. Face recognition experiments on FERET database demonstrate the effectiveness of our proposed approach.
Stabilization of alum-adjuvanted vaccine dry powder formulations: mechanism and application.

Studies were performed to elucidate the mechanism of alum gel coagulation upon freezing and drying and its relationship to vaccine potency loss and to develop a novel freeze-drying process for the production of stable alum-adjuvanted vaccine formulations suitable for conventional needle injection and epidermal powder immunization (EPI). The alum hydroxide-adjuvanted hepatitis-B surface antigen (Alum-HBsAg) and the alum phosphate-adjuvanted diphtheria and tetanus toxoids (Alum-DT) were dehydrated by freeze drying (FD), spray drying (SD), air drying (AD), or spray freeze drying (SFD). After drying by FD, SD, or AD, alum gels coagulated when examined by optical microscopy and particle size analysis. In addition, desorption of antigen molecules from the coagulated when examined by optical microscopy and particle size analysis. In addition, desorption of antigen molecules from the coagulated alum gel upon reconstitution appeared to be difficult, as indicated by attenuated band intensity on SDS-PAGE. In contrast, SFD alum gels turned a homogenous suspension upon reconstitution, suggesting minimal alum coagulation. In the mouse model, the in vivo immunogenicity of SFD Alum-HBsAg was preserved, whereas the FD Alum-HBsAg suffered significant immunogenicity loss. Grinding of coagulated FD Alum-HBsAg into smaller particles could partially recover the immunogenicity. In a guinea pig study using EPI, the SD Alum-DT formulation was not immunogenic, but the SFD Alum-DT formulations had a vaccine potency comparable to that of the untreated DT administered by I.M. injection. Overall, the relationship of coagulation of alum gel upon reconstitution and the loss of vaccine potency was established in this study. Alum gels became highly coagulated after dehydration by spray drying and traditional freeze-drying processes. However, freezing rate played a critical role in preserving the adjuvant effect of alum and fast freezing decreased the tendency of alum coagulation. Spraying the alum gel into liquid nitrogen represents the fastest freezing rate achievable and resulted in no discernible alum coagulation. Therefore, SFD presents a novel and effective drying process for alum-adjuvanted vaccine formulations and is particularly valuable for dry powder applications such as EPI.
Acute Kidney Injury After Cardiac Surgery: Focus on Modifiable Risk Factors

Background— Acute kidney injury (AKI) after cardiac surgery is a major health issue. Lacking effective therapies, risk factor modification may offer a means of preventing this complication. The objective of the present study was to identify and determine the prognostic importance of such risk factors. Methods and Results— Data from a multicenter cohort of 3500 adult patients who underwent cardiac surgery at 7 hospitals during 2004 were analyzed (using multivariable logistic regression modeling) to determine the independent relationships between 3 thresholds of AKI (>25%, >50%, and >75% decrease in estimated glomerular filtration rate within 1 week of surgery or need for postoperative dialysis) with death rates, as well as to identify modifiable risk factors for AKI. The 3 thresholds of AKI occurred in 24% (n=829), 7% (n=228), and 3% (n=119) of the cohort, respectively. All 3 thresholds were independently associated with a >4-fold increase in the odds of death and could be predicted with several perioperative variables, including preoperative intra-aortic balloon pump use, urgent surgery, and prolonged cardiopulmonary bypass. In particular, 3 potentially modifiable variables were also independently and strongly associated with AKI. These were preoperative anemia, perioperative red blood cell transfusions, and surgical reexploration. Conclusions— AKI after cardiac surgery is highly prevalent and prognostically important. Therapies aimed at mitigating preoperative anemia, perioperative red blood cell transfusions, and surgical reexploration may offer protection against this complication.
A practical local tomography reconstruction algorithm based on known subregion

A new method to reconstruct data acquired in a local tomography setup is proposed. This method uses an initial reconstruction and refines it by correcting the low-frequency artifacts, known as the cupping effect. A basis of Gaussian functions is used to correct the initial reconstruction. The coefficients of this basis are found by optimizing iteratively a fidelity term under the constraint of a known sub-region. Using a coarse basis reduces the degrees of freedom of the problem while actually correcting the cupping effect. Simulations show that the known region constraint yields an unbiased reconstruction, in accordance with uniqueness theorems stated in local tomography.