Miracle-dz/UniFAR-FTUs huggingface dataset:
Solving Symmetric Diagonally-Dominant Systems by Preconditioning

In this paper we design support-tree preconditioners for n × n matrices with m nonzeros that are symmetric and diagonally-dominant with a nonnegative diagonal (SDD matrix). This reduces to designing such a preconditioner for a Laplacian matrix, A, which can be interpreted as an undirected nonnegatively-weighted graph, G with n vertices and m edges. Preconditioners accelerate the convergence of iterative methods for solving linear systems, and our preconditioner allows us to analyze the convergence of a particular algorithm, due to Gremban and Miller, called support-tree conjugate gradient (STCG). An advantage of support-tree preconditioners is that STCG parallelizes well. We show that STCG equipped with our preconditioner requires O(m log n · √ dilexp(G)) work and O(m) space to solve the system Ax = b, where dilexp(G) is an edge-expansion-based upper bound on the diameter of G. Existing bounds depend only on the size of the matrix (graph), hence our bound is incomparable. For instance, if G is a bounded-degree expander graph with uniform edge weights, dilexp(G) = O(log 2 n), and the work is O(n log n). This is currently the best known bound for Laplacians of expander graphs. We show that dilexp(G) is always at most n, hence our bound is at most O(m √ n log n) for any Laplacian (or SDD) matrix. For sufficiently dense systems, when m = Ω(n), this bound offers the best known work guarantee of any linear-space method. The main technical contributions of this paper include (i) adapting a recent result of Racke to designing support-tree preconditioners, (ii) extending a power dissipation approach for bounding support numbers of preconditioners, and (iii) applying the methods used in Leighton and Rao’s approximate max-flow min-cut theorem to the “asymmetric” product flows the arise in Racke’s construction.
Measurement of Optical Properties of Small Particles

We have measured the optical constants of montmorillonite and the separated coats and cores of B. subtilis spores over the wavelength interval from 200 nm to 2500 nm. The optical constants of kaolin were obtained over the wavelength interval from 130 nm to 2500 nm. Our results are applicable to the development of systems for detection of airborne biological contaminants. Future work will include measurement of the optical constants of B. cereus spores, B. sub tilts vegetative cells, egg albumin, illite, and a mixture (by weight) of one third kaolin, one third montmorillonite, and one third illite.
Discovering governing equations from data by sparse identification of nonlinear dynamical systems

Significance Understanding dynamic constraints and balances in nature has facilitated rapid development of knowledge and enabled technology, including aircraft, combustion engines, satellites, and electrical power. This work develops a novel framework to discover governing equations underlying a dynamical system simply from data measurements, leveraging advances in sparsity techniques and machine learning. The resulting models are parsimonious, balancing model complexity with descriptive ability while avoiding overfitting. There are many critical data-driven problems, such as understanding cognition from neural recordings, inferring climate patterns, determining stability of financial markets, predicting and suppressing the spread of disease, and controlling turbulence for greener transportation and energy. With abundant data and elusive laws, data-driven discovery of dynamics will continue to play an important role in these efforts. Extracting governing equations from data is a central challenge in many diverse areas of science and engineering. Data are abundant whereas models often remain elusive, as in climate science, neuroscience, ecology, finance, and epidemiology, to name only a few examples. In this work, we combine sparsity-promoting techniques and machine learning with nonlinear dynamical systems to discover governing equations from noisy measurement data. The only assumption about the structure of the model is that there are only a few important terms that govern the dynamics, so that the equations are sparse in the space of possible functions; this assumption holds for many physical systems in an appropriate basis. In particular, we use sparse regression to determine the fewest terms in the dynamic governing equations required to accurately represent the data. This results in parsimonious models that balance accuracy with model complexity to avoid overfitting. We demonstrate the algorithm on a wide range of problems, from simple canonical systems, including linear and nonlinear oscillators and the chaotic Lorenz system, to the fluid vortex shedding behind an obstacle. The fluid example illustrates the ability of this method to discover the underlying dynamics of a system that took experts in the community nearly 30 years to resolve. We also show that this method generalizes to parameterized systems and systems that are time-varying or have external forcing.
Generalized Potts-Models and their Relevance for Gauge Theories ⋆

We study the Polyakov loop dynamics originating from finite-temperature Yang- Mills theory. The effective actions contain center-symmetric terms involving powers of the Polyakov loop, each with its own coupling. For a subclass with two couplings we perform a detailed analysis of the statistical mechanics involved. To this end we employ a modified mean field approximation and Monte Carlo simulations based on a novel cluster algorithm. We find excellent agreement of both approaches. The phase diagram exhibits both first and second order transitions between symmetric, ferromagnetic and antiferromagnetic phases with phase boundaries merging at three tricritical points. The critical exponents and at the continuous transition between symmetric and antiferromagnetic phases are the same as for the 3-state spin Potts model. Symmetry constraints and strong coupling expansion for the effective action describing the Polyakov loop dynamics of gauge theories lead to effective field theories with rich phase struc- tures. The fields are the fundamental characters of the gauge group with the fundamental domain as target space. The center symmetry of pure gauge theory remains a symmetry of the effective models. If one further freezes the Polyakov loop to the center Z of the gauge group one obtains the well known vector Potts spin-models, sometimes called clock models. Hence we call the effective theories for the Polyakov loop dynamics generalized Z-Potts models. We review our recent results on generalized Z3-Potts models (1). These results were obtained with the help of an improved mean field approximation and Monte Carlo simulations. The mean field approximation turns out to be much better than expected. Probably this is due to the existence of tricritical points in the effective theories. There exist four distinct phases and transitions of first and second order. The critical exponents and at the second order transition from the symmetric to antiferromagnetic phase for the generalized Potts model are the same as for the
Ab initio calculation of the phase stability, mechanical properties and electronic structure of ZrCr2 Laves phase compounds

Ab initio calculations have been used to investigate the phase stability, mechanical properties and electronic structure of ZrCr2 Laves phase compounds, based on the method of augmented plane waves plus local orbitals with the generalized gradient approximation. The calculated lattice constants for the C15, C36 and C14 structures are in good agreement with experimental values. The calculation of heats of formation showed that C15 is a ground-state phase, whereas C36 is an intermediate phase and C14 the high-temperature phase. The elastic constants and elastic moduli for the C15 structure were calculated systematically and compared with experiments and previous theoretical calculations. The intrinsic and extrinsic stacking fault energies are found to be 112 and 98 mJ m−2, respectively. The equilibrium separations between Schockley are also predicted using the calculated elastic moduli and stacking fault energies. Finally, the calculated electronic structures of these Laves phases are discussed based on these results.
The prevalence of chronic fatigue syndrome/ myalgic encephalomyelitis: a meta-analysis

Purpose To perform a meta-analysis to examine variability among prevalence estimates for CFS/ME, according to the method of assessment used. Methods Databases were systematically searched for studies on CFS/ME prevalence in adults that applied the 1994 Centers for Disease Control (CDC) case definition.1 Estimates were categorized into two methods of assessment: self-reporting of symptoms versus clinical assessment of symptoms. Meta-analysis was performed to pool prevalences by assessment using random effects modeling. This was stratified by sample setting (community or primary care) and heterogeneity was examined using the I2 statistic. Results Of 216 records found, 14 studies were considered suitable for inclusion. The pooled prevalence for self-reporting assessment was 3.28% (95% CI: 2.24–4.33) and 0.76% (95% CI: 0.23–1.29) for clinical assessment. High variability was observed among self-reported estimates, while clinically assessed estimates showed greater consistency. Conclusion The observed heterogeneity in CFS/ME prevalence may be due to differences in method of assessment. Stakeholders should be cautious of prevalence determined by the self-reporting of symptoms alone. The 1994 CDC case definition appeared to be the most reliable clinical assessment tool available at the time of these studies. Improving clinical case definitions and their adoption internationally will enable better comparisons of findings and inform health systems about the true burden of CFS/ME.
THE JOINT HURRICANE TEST BED Its First Decade of Tropical Cyclone Research-To-Operations Activities Reviewed

The Joint Hurricane Testbed (JHT) is reviewed at the completion of its first decade. Views of the program by hurricane forecasters at the National Hurricane Center, the test bed's impact on forecast accuracy, and highlights of the top-rated projects are presented. Key concerns encountered by the test bed are identified as possible “lessons learned” for future research-to-operations efforts. The paper concludes with thoughts on the potential changing role of the JHT.
' s response to reviews Title : Cognitive performance in relapsing remitting multiple sclerosis : a longitudinal study in daily practice using a brief computerized cognitive battery

Explain that Power of Attention etc are subtests from the CDR and what they measure. We have clarified the ‘domain’ assessed by each measure as well as the derivation in the Methods section. In addition, detailed task descriptions and composite score derivations appear in the additional files 1 and 2. Explain who are the controls, this is very important. Otherwise the d values are meaningless. We have clarified in the Abstract, Results and Discussion sections that these normative data are derived from healthy volunteers enrolled in prior clinical trials and not a control group from the present study. In addition, some of the potential caveats of such a comparison are now noted in the discussion. Stable is not defined, do you mean that the mean values did not change, good test-retest reliability? The term ‘stable’ has been removed to avoid any ambiguity.
Fracture Mechanical Behavior of Aggregate–Cement Matrix Interfaces

Cracks in concrete tend to run along cement-aggregate interfaces. In fact, these interfaces serve as the weak links. In this paper, the adhesion between cement matrix and aggregate is quantitatively expressed by using the specific-fracture-energy concept. The specific fracture energy is obtained from the load-displacement curve of the wedge-splitting test. Smooth and dense limestone and porous, rough sandstone were used in the experiments to cover a broad range of aggregate materials. Based on the experiments, investigators conclude that specific fracture energy provides a useful tool for the fracture characterization of interfaces in cement composites.
Degradation of Anthracene by Bacteria Isolated from Oil Polluted Tropical Soils

Four bacteria, identified as Pseudomonas aeruginosa, Alcaligenes eutrophus, Bacillus subtilis and Micrococcus'luteus were isolated from crude oil polluted soils using anthracene as the sole carbon and energy source. All the organisms utilized n-hexadecane, n-tetradecane, diesel oil, engine oil and naphthalene as sole carbon sources. None could utilize hexane, cycloheptane, xylene, benzene, toluene, phenol, fluoranthene,and kerosene as carbon sources. Highest cell density obtained with 0.1% (w/v) anthracene were 4.5 × 107 (cfu/ml), 8.6 × 106 (cfu/ml), 5.4 × 106 and 2.4 × 106 (cfu/ml) respectively, for P. aeruginosa, A. eutrophus, B. subtilis and M. luteus after 30 days incubation. Growth of the organism s on a Nigerian crude oil resulted in a residual oil concentration of 22.2% , 33.3% , 39.3% ,44% and 91.7% respectively, for P. aeruginosa, A. eutrophus, B. subtilis, M. luteus and the noninoculated control on the 14 th day. Ring fission enzymes of the meta pathway were detected in induced cells of P. aeruginosa and A. eutrophus while ortho pathway enzymes were detected in B. subtilis and M. luteus. P. aeruginosa and A. eutrophus had specific catechol-2,3-dioxygenase activities of 3.8 ± 0.183 and 0.64 ± 0.032 μmol / min × mg protein respectively while catechol-1,2-dioxygenase activities of 1.95 ± 0.029 and 1.89 ± 0.026 μmol / min x mg protein were detected in B. subtilis and M. luteus respectively. This work , highlights the capability of these unreported tropical strains of A. eutrophus, B. subtilis and M. luteus as anthracene degraders.
Cortical Blindness, Transient and Otherwise, Associated with Detachable Coil Embolization of Intracranial Aneurysms

BACKGROUND AND PURPOSE: Cortical visual loss is a rare complication of cerebral angiography without a definitive pathophysiology. Given the rapid increase in endovascular procedures used to treat cerebral aneurysms, we explored the prevalence of this complication and whether we could add to the understanding of this disorder. Materials and METHODS: We performed a retrospective review of all procedures performed with the same contrast agent and detachable coils for treatment of posterior circulation aneurysms by 1 endovascular surgery service from 1996 to 2006. All patients were evaluated before and after each procedure by a team that included a neuro-ophthalmologist. RESULTS: Of 137 intra-arterial treatment procedures performed for posterior circulation aneurysms, we identified 4 patients with cerebral vision loss complications. During the same time period, >500 aneurysms of the anterior cerebral circulation were treated without this complication. The visual field loss was unilateral in 2 and bilateral in 2 patients. Recovery was complete in 3 and almost normal in the fourth patient. The amount of contrast used and the duration of the procedure were similar among all patients. The 4 patients had no identified specific risk factors for developing procedure-associated occipital dysfunction, all 4 had undergone prior angiography, and 1 patient had undergone repeat coiling, without complication. CONCLUSION: The 2.9% prevalence of cerebral visual loss with endovascular coil treatment of posterior circulation aneurysms is higher than that for angiography alone. Our patients recovered well with corticosteroid and intravenous hydration treatment. Recognizing the self-limiting nature of this problem might prevent an unneeded intervention.
Evidence for the hallmarks of human aging in replicatively aging yeast

Recently, efforts have been made to characterize the hallmarks that accompany and contribute to the phenomenon of aging, as most relevant for humans 1. Remarkably, studying the finite lifespan of the single cell eukaryote budding yeast (recently reviewed in 2 and 3) has been paramount for our understanding of aging. Here, we compile observations from literature over the past decades of research on replicatively aging yeast to highlight how the hallmarks of aging in humans are present in yeast. We find strong evidence for the majority of these, and summarize how yeast aging is especially characterized by the hallmarks of genomic instability, epigenetic alterations, loss of proteostasis, deregulated nutrient sensing, and mitochondrial dysfunction.
In vivo, trans‐synaptic tract‐tracing utilizing manganese‐enhanced magnetic resonance imaging (MEMRI)

It is well established that manganese ion (Mn2+) can access neurons through voltage‐gated calcium (Ca2+) channels. Based upon this fundamental principle, Mn2+ has long been used in biomedical research as an indicator of Ca2+ influx in conjunction with fluorescent microscopy. Additionally, after entry into neurons, Mn2+ is transported down axons via microtubule based fast axonal transport. Furthermore, Mn2+ is paramagnetic, resulting in a shortening of the spin‐lattice relaxation time‐constant, T1, which yields positive contrast enhancement in T1‐weighted MRI images, specific to tissues where the ion has accumulated. Manganese‐enhanced MRI (MEMRI) utilizes a combination of these properties of Mn2+ to trace neuronal pathways in an MRI‐detectable manner. The focus of this review will detail some of the current MEMRI tract‐tracing methodologies in mice and non‐human primates as well as biological applications of MEMRI tract‐tracing. Copyright © 2004 John Wiley & Sons, Ltd.
STACKS AND SHEAVES OF CATEGORIES AS FIBRANT OBJECTS, II

We show that the category of categories bred over a site is a generalized Quillen model category in which the weak equivalences are the local equivalences and the brant objects are the stacks, as they were dened by J. Giraud. The generalized model category restricts to one on the full subcategory whose objects are the categories bred in groupoids. We show that the category of sheaves of categories is a model category that is Quillen equivalent to the generalized model category for stacks and to the model category for strong stacks due to A. Joyal and M. Tierney.
Role of the Neighbourhood Deprivation in the Adverse Effect of Air Pollution on Congenital Abnormalities

Congenital abnormalities (CAs) remain a major cause of stillbirth and neonatal mortality. The literature has shown that congenital malformations are suggested to have multifactorial determinants, including environmental exposures and socioeconomic patterns. Moreover, since a decade, combined effects of environmental and socioeconomic characteristics are suspected to have an impact on the risk of congenital anomalies. Three mechanisms have been proposed in the literature suggesting the possible combined effect of the social health inequalities and the environmental exposures. This commentary presents the role of the neighbourhood deprivation in the adverse effect of air pollution on congenital anomalies. Both air pollution and neighbourhood deprivation have been reported in the literature to increase the risk of congenital abnormalities.
Bayesian Inference for Multivariate Ordinal Data Using Parameter Expansion

Multivariate ordinal data arise in many applications. This article proposes a new, efficient method for Bayesian inference for multivariate probit models using Markov chain Monte Carlo techniques. The key idea is the novel use of parameter expansion to sample correlation matrices. A nice feature of the approach is that inference is performed using straightforward Gibbs sampling. Bayesian methods for model selection are also discussed. Our approach is motivated by a study of how women make decisions on taking medication to reduce the risk of breast cancer. Furthermore, we compare and contrast the performance of our approach with other methods.
Direct Household Rebound Effect for Electricity Consumption in the U . S . : Implications for Energy Conservation Policy

The direct rebound effect is a concept that describes the increase in consumer demand for energy services resulting from improvements in energy efficiency. This paper uses household electricity consumption data in the United States during the period 2006-2010 to generate an estimation of the rebound effect indirectly through price elasticities. It then analyzes the impact of state level appliance standards and building code standards in order to inform energy policy. Findings suggest that energy conservation policymakers should redirect their current efforts to impose more stringent appliance standards toward standards that are not subject to a considerable household rebound effect such as building codes.
Testing not-so-obvious models of healthcare quality.

PURPOSE The purpose of this paper is to show that, although there has been some research to identify the dimensions on which healthcare quality and in-patient satisfaction should be measured, the confirmation of constructs and indicators that constitute an overall care quality and satisfaction remains unclear. The objective is to present several models of service quality and satisfaction in healthcare for discharged patients; and to test those models in a sample of discharged patients in public hospitals in the United Arab Emirates. DESIGN/METHODOLOGY/APPROACH A detailed in-patient survey (using interviews) was used. Data were collected with questionnaires from adult discharges (n = 244) in public hospitals in the UAE. Several structures are proposed and tested. Confirmatory Factor Analysis (CFA) and LISREL SIMPLIS using maximum likelihood estimation were used to estimate and test the parameters of the hypothesized models derived deductively from the previous literature. FINDINGS Several models (with one, two, three and four constructs) with different structures were tested using CFA. The final recommended model is based on three constructs--quality of care, process and administration, and information. The goodness-of-fit statistics supported the basic solution of the healthcare quality-satisfaction model. ORIGINALITY/VALUE The model has been found to capture attributes that characterize healthcare quality in a developing country such as the UAE and could represent other modern healthcare systems. It can be used as a basis for evaluation in healthcare practices from discharges (in-patients) point of view. The study highlights the importance of patients' satisfaction with care as predictors of quality of care. The results also confirm the construct validity of the previously discussed healthcare quality scales.
Relationship between GSTP1 Ile(105)Val polymorphism and docetaxel-induced peripheral neuropathy: clinical evidence of a role of oxidative stress in taxane toxicity.

BACKGROUND Glutathione-S-transferases (GST) regulate the cellular response to oxidative stress. We previously highlighted the importance of oxidative stress in taxane toxicity and therefore investigated the relationship between the GST isoforms M1, T1 and P1 gene polymorphisms and docetaxel (Taxotere)-induced peripheral neuropathy (DIPN). PATIENTS AND METHODS The GSTM1 (null), GSTT1 (null) and GSTP1 (Ile(105)Val and Ala(114)Val) polymorphisms were determined in a cohort of cancer patients treated with docetaxel and entered in a clinical trial database. The relationship between GST polymorphisms and grade > or = 2 DIPN as primary end point was studied. RESULTS Fifty-eight patients (median age 61 years) received a total of 261 cycles of docetaxel given as single agent. Patients with GSTP1 (105)Ile/(105)Ile genotype had a higher risk of developing a grade > or = 2 DIPN than did those with other GSTP1 genotypes (8 of 27 versus 2 of 31, respectively, odds ratio 6.11; 95% confidence interval 1.17-31.94; P = 0.03). In multivariate analysis, grade > or = 2 DIPN was strongly correlated with GSTP1 (105)Ile/(105)Ile genotype (P = 0.01) and the number of cycles (P = 0.03). CONCLUSION We found a significant correlation between GSTP1 (105)Ile/(105)Ile genotype and the development of grade > or = 2 DIPN. This finding strongly suggests a role of oxidative stress in the pathophysiology of DIPN.