Miracle-dz/UniFAR-FTUs huggingface dataset:
Vegetation Type and Age Drive Changes in Soil Properties, Nitrogen, and Carbon Sequestration in Urban Parks under Cold Climate

Urban green spaces provide ecosystem properties fundamental to the provision of ecosystem services, such as the sequestration of carbon and nutrients and serving as a reservoir for organic matter. Although urban vegetation influences soil physico-chemical properties, it remains unknown whether ecosystem properties depend on plant species portfolios. We tested the influence of three common functional plant groups (evergreen trees, deciduous trees, grass/lawn) for their ability to modify soils in parks of various ages under cold climatic conditions in Finland. We hypothesized that (i) plant functional groups affect soils differently resulting in divergent ecosystem properties, and (ii) that these ecosystem properties also depend on park age. We included 41 urban parks of varying ages (10, 50 and > 100 years) and additional control forests. Park soils were sampled for physico-chemical parameters up to 50 cm depth. Our data indicate that plant functional groups modify soils differently, especially between the evergreen and lawn treatments at 50 and > 100 year old parks. Soils under evergreen trees had the lowest pH and generally the highest percentage organic matter, percentage total carbon and percentage total nitrogen. Soil pH remained the same, whereas concentrations of organic matter, total carbon and total nitrogen declined by depth. Soils in the reference forests had lower pH but higher percentages organic matter, total carbon and total nitrogen than those in parks. We estimate that old parks with evergreen trees can store 35.5 kg C m-2 and 2.3 kg N m-2 – considerably more than in urban soils in warmer climates. Our data suggest that plant-soil interactions in urban parks, in spite of being constructed environments, are surprisingly similar to those in natural forests.
Black Networks After Emancipation : Evidence from Reconstruction and the Great Migration ∗

We find that southern blacks responded collectively to political and economic opportunities after Emancipation, but only in places where specific conditions were satisfied. Blacks would have lived and worked in close proximity to each other in counties where labor intensive plantation crops were grown. Spatial proximity would have resulted in more connected social networks. These connected networks would have supported the formation of larger coalitions of black activists during Reconstruction and larger coalitions of black workers moving together to northern cities during the Great Migration. Our theoretical model places additional structure on this relationship. Coalitions will not form and there will be no association between network connectedness and the outcomes of interest – political participation and migration – up to a threshold, followed by a positive association above the threshold. Voting and migration patterns across counties are consistent with the theory there is no association with our crop-based measure of network connectedness up to a threshold point at which a steep, monotonic relationship begins. This finding is robust to rigorous testing, and these tests show that competing hypotheses do not exhibit similar nonlinear patterns. Blacks from southern counties where plantation crops were grown accounted for a disproportionate share of northern migrants, and these migrants appear to have benefited from network externalities, as they moved to the same destination cities.
NFATc3-Induced Reductions in Voltage-Gated K+ Currents After Myocardial Infarction

Reductions in voltage-activated K+ (Kv) currents may underlie arrhythmias after myocardial infarction (MI). We investigated the role of β-adrenergic signaling and the calcineurin/NFAT pathway in mediating the reductions in Kv currents observed after MI in mouse ventricular myocytes. Kv currents were produced by the summation of 3 distinct currents: Ito, IKslow1, and IKslow2. At 48 hours after MI, we found a 4-fold increase in NFAT activity, which coincided with a decrease in the amplitudes of Ito, IKslow1, and IKslow2. Consistent with this, mRNA and protein levels of Kv1.5, 2.1, 4.2, and 4.3, which underlie IKslow1, IKslow2, and Ito, were decreased after MI. Administration of the β-blocker metoprolol prevented the activation of NFAT and the reductions in Ito, IKslow1, and IKslow2 after MI. Cyclosporine, an inhibitor of calcineurin, also prevented the reductions in these currents after MI. Importantly, Kv currents did not change after MI in ventricular myocytes from NFATc3 knockout mice. Conversely, chronic β-adrenergic stimulation or expression of an activated NFATc3 decreased Kv currents to a similar extent as MI. Taken together, these data indicate that NFATc3 plays an essential role in the signaling pathway leading to reduced Ito, IKslow1, and IKslow2 after MI. We propose that increased β-adrenergic signaling after MI activates calcineurin and NFATc3, which decreases Ito, IKslow1, and IKslow2 via a reduction in Kv1.5, Kv2.1, Kv4.2, and Kv4.3 expression.
Effect of topical application of melatonin on serum levels of C-reactive protein (CRP), interleukin-6 (IL-6) and tumor necrosis factor-alpha (TNF-α) in patients with type 1 or type 2 diabetes and periodontal disease

Background The present clinical trial study was designed to assess the effect of topical application of melatonin on serum levels of tumor necrosis factor-alpha (TNF-α), interleukin-6 (IL-6) and C-reactive protein (CRP) in patients with diabetes and periodontal disease in comparison with healthy controls. Material and Methods Serum levels of TNF-α and IL-6 were measured by enzyme-linked immunosorbent assay and CRP by nephelometry by using the proper commercial kits in 30 patients with diabetes and periodontal disease, and also in a control group of 30 healthy subjects. Periodontograms were performed using the Florida Probe®. Patients with diabetes were treated with a topical application of melatonin (1% orabase cream formula) once daily for 20 days. Healthy subjects were treated with a placebo orabase cream. Results Patients with diabetes and periodontal disease had significantly higher mean levels of serum TNF-α, IL-6 and CRP than healthy subjects (P < 0.001). Following topical melatonin application, there was a statistically significant decrease in the gingival index and pocket depth (P < 0.001) as well as a significant decrease in IL-6 and CRP serum levels (P < 0.001). Local melatonin application in patients with diabetes and periodontal disease resulted in a significant decrease in CRP and IL-6 serum levels as well as an improvement in the gingival index and pocket depth. Patients with periodontal disease had significantly higher serum CRP, IL-6 and TNF-α values by comparison with healthy subjects. Conclusions We conclude that melatonin can modulate the inflammatory action of these molecules in periodontal patients. Key words:Melatonin, periodontal disease, diabetes mellitus, interleukin-6, tumor necrosis factor-alpha, C-reactive protein, inflammatory markers.
Network Plasticity as Bayesian Inference

General results from statistical learning theory suggest to understand not only brain computations, but also brain plasticity as probabilistic inference. But a model for that has been missing. We propose that inherently stochastic features of synaptic plasticity and spine motility enable cortical networks of neurons to carry out probabilistic inference by sampling from a posterior distribution of network configurations. This model provides a viable alternative to existing models that propose convergence of parameters to maximum likelihood values. It explains how priors on weight distributions and connection probabilities can be merged optimally with learned experience, how cortical networks can generalize learned information so well to novel experiences, and how they can compensate continuously for unforeseen disturbances of the network. The resulting new theory of network plasticity explains from a functional perspective a number of experimental data on stochastic aspects of synaptic plasticity that previously appeared to be quite puzzling.
A Nonparametric Bayesian Approach for Spoken Term Detection by Example Query

State of the art speech recognition systems use data-intensive context-dependent phonemes as acoustic units. However, these approaches do not translate well to low resourced languages where large amounts of training data is not available. For such languages, automatic discovery of acoustic units is critical. In this paper, we demonstrate the application of nonparametric Bayesian models to acoustic unit discovery. We show that the discovered units are correlated with phonemes and therefore are linguistically meaningful. We also present a spoken term detection (STD) by example query algorithm based on these automatically learned units. We show that our proposed system produces a P@N of 61.2% and an EER of 13.95% on the TIMIT dataset. The improvement in the EER is 5% while P@N is only slightly lower than the best reported system in the literature.
A two‐year longitudinal study of post‐stroke mood disorders: findings during the initial evaluation.

A consecutive series of 103 stroke patients capable of undergoing a psychiatric interview were evaluated for mood disorders. Nearly 50% of patients studied in the acute stroke period had clinically significant depressions and one fourth had symptom clusters found in major depressive disorders. We confirmed our previous findings that lesion location is most important in determining frequency and severity of depression. In addition, we have identified other variables including functional physical impairment, intellectual impairment, quality of social support, and age which contribute to or modify depression. Post-stroke depressive disorders are multifactorial in their determination and expression and include both neurophysiological-neurochemical mechanisms and psychological factors in their etiology.
The influence of heating on the nutritive value of soya-bean meal for ruminants

I t has been generally assumed that the nutritive value of protein feeds for ruminant animals is not influenced by the chemical and physical properties of the proteins. Several recent investigations have shown that proteins with a high solubility are degraded in the rumen to ammonia at a rate too rapid for efficient utilization. The rumen micro-organisms can then utilize only a relatively small part of the liberated ammonia for synthetic purposes. Excess ammonia diffuses into the blood and is converted in the liver into urea, and most of this urea is excreted in the urine, only a small amount being returned to the rumen through the saliva. Evidence was given by El-Shazly (1958) and Jasiorowski (1960) that the protein in green forages and hays is utilized to a greater extent when it is of low solubility, highly soluble proteins from similar feeds being utilized to a lesser degree. The beneficial effect of reducing the solubility of protein in concentrates by heating was first recognized by Chalmers, Cutherbertson & Synge (1954) and Chalmers & Synge (1954), and confirmed by Whitelaw, Preston & Dawson (1961) who found considerable advantage in the use of heat-treated groundnut meal in comparison with untreated groundnut meal. I t is well known that the full utilization of soya-bean meal for poultry feeding is obtained only by proper heating. The causes generally recognized as responsible for the improvement of soya-bean meal by heat treatment are irrelevant for ruminants. Since the solubility of protein of soya-bean meal decreases considerably on heating, we compared the utilization by ruminants of protein of soya-bean meals subjected to different heat treatments. Preliminary experiments carried out in a miniature artificial rumen showed a very significant decrease in the amount of ammonia liberated from heated soya-bean meal in comparison with the untreated soya-bean meal. These results led us to examine the utilization by sheep of three different kinds of soya-bean meal, the rate of liberation of ammonia in the rumen, changes in blood-urea concentration and nitrogen balance being used for assessing their value.
LOX Mutations Predispose to Thoracic Aortic Aneurysms and Dissections.

RATIONALE Mutations in several genes have been identified that are responsible for 25% of families with familial thoracic aortic aneurysms and dissections. However, the causative gene remains unknown in 75% of families. OBJECTIVES To identify the causative mutation in families with autosomal dominant inheritance of thoracic aortic aneurysms and dissections. METHODS AND RESULTS Exome sequencing was used to identify the mutation responsible for a large family with thoracic aortic aneurysms and dissections. A heterozygous rare variant, c.839G>T (p.Ser280Arg), was identified in LOX, encoding a lysyl oxidase, that segregated with disease in the family. Sanger and exome sequencing was used to investigate mutations in LOX in an additional 410 probands from unrelated families. Additional LOX rare variants that segregated with disease in families were identified, including c.125G>A (p.Trp42*), c.604G>T (p.Gly202*), c.743C>T (p.Thr248Ile), c.800A>C (p.Gln267Pro), and c.1044T>A (p.Ser348Arg). The altered amino acids cause haploinsufficiency for LOX or are located at a highly conserved LOX catalytic domain, which is relatively invariant in the population. Expression of the LOX variants p.Ser280Arg and p.Ser348Arg resulted in significantly lower lysyl oxidase activity when compared with the wild-type protein. Individuals with LOX variants had fusiform enlargement of the root and ascending thoracic aorta, leading to ascending aortic dissections. CONCLUSIONS These data, along with previous studies showing that the deficiency of LOX in mice or inhibition of lysyl oxidases in turkeys and rats causes aortic dissections, support the conclusion that rare genetic variants in LOX predispose to thoracic aortic disease.
Variational Inference using Implicit Distributions

Generative adversarial networks (GANs) have given us a great tool to fit implicit generative models to data. Implicit distributions are ones we can sample from easily, and take derivatives of samples with respect to model parameters. These models are highly expressive and we argue they can prove just as useful for variational inference (VI) as they are for generative modelling. Several papers have proposed GAN-like algorithms for inference, however, connections to the theory of VI are not always well understood. This paper provides a unifying review of existing algorithms establishing connections between variational autoencoders, adversarially learned inference, operator VI, GAN-based image reconstruction, and more. Secondly, the paper provides a framework for building new algorithms: depending on the way the variational bound is expressed we introduce prior-contrastive and joint-contrastive methods, and show practical inference algorithms based on either density ratio estimation or denoising.
EFFECT OF IMMUNOSUPPRESSION ON CHRONIC LCM VIRUS INFECTION OF MICE

C3H mice chronically infected with LCM virus were found to be lethally affected by small doses of immunosuppression which caused bone marrow aplasia but had no effect on the amount of virus carried by the mouse. Humoral immune response of SWR/J mice to acute LCM infection was found to be totally suppressed by repeated single doses of 300 R/wk with no alteration in the level of virus carried by the mouse. In contrast, the established anti-LCM humoral immune response encountered in mice chronically infected with LCM virus was not suppressed by the same irradiation procedure. Over half of the chronic LCM carrier SWR/J mice treated with cyclophosphamide for 6 mo had total anti-LCM humoral immunosuppression, but showed no change in the level of virus carried. The glomerulonephritis which occurs in chronic LCM carrier mice was prevented by cyclophosphamide treatment in 90% of the mice. The humoral immune response which occurs in chronic LCM carrier mice appears to play no role in controlling the amount of virus carried by the mouse. Suppression of the LCM immune response by cyclophosphamide does prevent the development of glomerulonephritis in these mice.
A two-step Recommendation Algorithm via Iterative Local Least Squares

Recommender systems can change our life a lot and help us select suitable and favorite items much more conveniently and easily. As a consequence, various kinds of algorithms have been proposed in last few years to improve the performance. However, all of them face one critical problem: data sparsity. In this paper, we proposed a two-step recommendation algorithm via iterative local least squares (ILLS). Firstly, we obtain the ratings matrix which is constructed via users' behavioral records, and it is normally very sparse. Secondly, we preprocess the "ratings" matrix through ProbS which can convert the sparse data to a dense one. Then we use ILLS to estimate those missing values. Finally, the recommendation list is generated. Experimental results on the three datasets: MovieLens, Netflix, RYM, suggest that the proposed method can enhance the algorithmic accuracy of AUC. Especially, it performs much better in dense datasets. Furthermore, since this methods can improve those missing value more accurately via iteration which might show light in discovering those inactive users' purchasing intention and eventually solving cold-start problem.
ACID MUCOSUBSTANCE AND BASIC PROTEIN IN MOUSE PANETH CELLS

The histochemistry of mouse Paneth cell granules was investigated with alcian blue (AB, pH 1.0 or 2.5), periodic acid-Schiff reagent (PAS), high iron diamine (HID) and Biebrich scarlet (pH 9.5). After formalin fixation, an AB pH 2.5-PAS sequence demonstrates alcianophilic rims surrounding weakly PAS-reactive granule cores; the HID-AB and AB pH 1.0-PAS sequences show peripheral staining indicative of a sulfomucin in most granules and a carboxymucin in some granules, the latter predominantly in the distal small intestine. When stained with PAS alone, rims of Paneth granules stain intensely and cores weakly. After HgC12 fixation, HID staining indicative of sulfomucin occurs in the cores of most granules and in the rims of many granules. An AB-Biebrich scarlet sequence shows acid mucosubstance in the rims and strongly basic protein (presumably arginine rich) in the cores of the granules. The basic protein-rich cores are larger toward the bottom of the crypts and toward the distal small intestine. The acid mucosaccharide-rich rims appear thinner surrounding the larger granules at the bottom of the crypts. Fine structural studies have demonstrated dialyzed iron staining indicative of acid mucosubstance in the rims of mouse Paneth cell granules and in small profiles and some lamellae of the Golgi zone.
Multivariate log-concave distributions as a nearly parametric model

Abstract In this paper we show that the family Pd(lc) of probability distributions on ℝd with log-concave densities satisfies a strong continuity condition. In particular, it turns out that weak convergence within this family entails (i) convergence in total variation distance, (ii) convergence of arbitrary moments, and (iii) pointwise convergence of Laplace transforms. In this and several other respects the nonparametric model Pd(lc) behaves like a parametric model such as, for instance, the family of all d-variate Gaussian distributions. As a consequence of the continuity result, we prove the existence of nontrivial confidence sets for the moments of an unknown distribution in Pd(lc). Our results are based on various new inequalities for log-concave distributions which are of independent interest.
The Determinants of International Investment and Attention Allocation: Using Internet Search Query Data

This paper explores the joint determination of home bias and attention allocation. We overcome the typical challenge associated with evaluating attention allocation theories by using a new internet search query dataset to measure how much information investors decide to process. Employing an instrumental variables approach, we find empirical evidence of a two-way causality between home bias and attention. Our estimates suggest that if all countries were to receive the same level of attention as the U.S., then the average home bias by U.S. investors would fall from 85.2% to 57.3%.
Availability of on-site catheterization and clinical outcomes in patients receiving fibrinolysis for ST-elevation myocardial infarction.

AIMS To compare management and clinical outcomes in hospitals stratified by the availability of on-site catheterization in InTIME-II, a multicentre trial comparing alteplase with lanoteplase for acute myocardial infarction. METHODS AND RESULTS We studied 15,078 patients enrolled in 35 countries and 855 hospitals. Thirty-one percent of hospitals had 24-h, 25% day-only, and 44% no on-site catheterization facilities. Rates of cardiac angiography (57%, 38%, 26%) and revascularization (37%, 21%, 17%) were higher in hospitals with increasing access to on-site facilities(P<0.0001). The presence of a 24-h on-site facility was the strongest predictor of angiography during the index admission (odds ratio 4.17, 95% CI 3.85-4.54). There were no major differences in patient outcomes at 30 days when hospitals were stratified by availability of on-site catheterization. Adjusted 1-year mortality was similar between groups of hospitals (odds ratio for day-only 0.94 [0.80-1.09] and odds ratio for no availability 0.95 [0.83-1.10] compared to hospitals with 24-h facilities). CONCLUSIONS There is a marked variation in procedure use by the availability of on-site catheterization with no major differences in patient outcomes. There is a need for additional randomized trials in the current era to address both the appropriate selection of patients and timing of invasive procedures in ST-elevation acute myocardial infarction.
A refactoring-based approach for test case selection and prioritization

Refactoring edits, commonly applied during software development, may introduce faults in a previously-stable code. Therefore, regression testing is usually applied to check whether the code maintains its previous behavior. In order to avoid rerunning the whole regression suite, test case prioritization techniques have been developed to order test cases for earlier achievement of a given goal, for instance, improving the rate of fault detection during regression testing execution. However, as current techniques are usually general purpose, they may not be effective for early detection of refactoring faults. In this paper, we propose a refactoring-based approach for selecting and prioritizing regression test cases, which specializes selection/prioritization tasks according to the type of edit made. The approach has been evaluated through a case study that compares it to well-known prioritization techniques by using a real open-source Java system. This case study indicates that the approach can be more suitable for early detection of refactoring faults when comparing to the other prioritization techniques.