Miracle-dz/UniFAR-FTUs huggingface dataset:
Too Fast Causal Inference under Causal Insufficiency

Causally insufficient structures (models with latent or hidden variables, or with confounding etc.) of joint probability distributions have been subject of intense study not only in statistics, but also in various AI systems. In AI, belief networks, being representations of joint probability distribution with an underlying directed acyclic graph structure, are paid special attention due to the fact that efficient reasoning (uncertainty propagation) methods have been developed for belief network structures. Algorithms have been therefore developed to acquire the belief network structure from data. As artifacts due to variable hiding negatively influence the performance of derived belief networks, models with latent variables have been studied and several algorithms for learning belief network structure under causal insufficiency have also been developed. Regrettably, some of them are known already to be erroneous (e.g. IC algorithm of [Pearl:Verma:91]. This paper is devoted to another algorithm, the Fast Causal Inference (FCI) Algorithm of [Spirtes:93]. It is proven by a specially constructed example that this algorithm, as it stands in [Spirtes:93], is also erroneous. Fundamental reason for failure of this algorithm is the temporary introduction of non-real links between nodes of the network with the intention of later removal. While for trivial dependency structures these non-real links may be actually removed, this may not be the case for complex ones, e.g. for the case described in this paper. A remedy of this failure is proposed.
An Interval Expectation Maxi m ization Algorith m for Outlier Detection in Linear Regression

Outlier detection has an important role in diverse fields of research and application domains including pattern recognition, exploratory data analysis and data mining. In classical regression analysis, these outliers are often removed from the data set, being usually regarded as errors of the process. However, in SDA domain, this procedure is unsuitable because a single symbolic data observation may represent the generalization of a subset of other classical observations. This paper introduces an expectation-maximization algorithm for interval data in order to detect atypical intervals concerned with regression analysis problems. The algorithm is evaluated regarding different simulated and real interval data sets.
Insulin-like Activity of Dilute Human Serum Assayed by an Isolated Adipose Cell Method

A method for insulin assay using isolated adipose cells is described. Fat cells incubated in Krebs-Ringer bicarbonate buffer containing glucose (0.1 mg. per ml.) and albumin (5 per cent) converted glucose-l-14-C to Co2. Addition of insulin caused a maximal stimulation of about eight- to sixteen-fold of the Co2 production. The dose-response relationship exhibited a typical sigmoid shaped curve. The minimum detectable insulin concentration was about 2-5 μU. per ml. ; the maximum response was obtained with insulin concentrations of about 300 to 600 μU. per ml. In the optimal range (about 20 to 160 μU. per ml.) the insulin concentrations were determined with a precision of about ±10 per cent (four replications). This method was applied to human serum. It appeared that dilute (1 per cent), dialyzed, fasting serum contained large amounts of “insulin-like” activity (about 20 to 70 μU. per ml.). The dose response relationship of dialyzed serum in a concentration less than about 2 per cent paralleled that of insulin. The increment in Co2 production with greater serum concentrations was less than the increment with greater insulin concentrations. The insulin-like activity of 1 per cent serum did not change after an intravenous glucose load; it was not suppressed by addition of insulin antibodies. Fractionation of serum by starch block electrophoresis located all of the activity in a broad peak in the (β-γ globulin region. Insulin added to serum was quantitatively recovered in a separate peak located in the slower moving component of the albumin fraction. When serum was subjected to gel nitration on Sephadex G 75 the “insulin-like” activity emerged with the total excluded fraction whereas insulin added to serum was retarded on the column. These properties were similar to those of the previously described “atypical” insulin. Its nature remained undefined.
The ultrasound neck imaging for tracheostomy study: A study prompting ultrasound screening prior to percutaneous tracheostomy procedures to improve patient outcomes

Introduction Percutaneous tracheostomy procedures are commonplace in intensive care units worldwide. Haemorrhagic complications, though potentially fatal, are thought to be under-reported. Ultrasonography use has not established itself in these procedures. This study assesses the prevalence and characteristics of pre-tracheal blood vessels, to aid intensivists on potential procedural hazards. Method A retrospective, observational study was performed in the UK. Computed tomography angiograms from January 2012 to October 2014 were randomly retrieved and analysed for vessel data. Results A total of 343 adult patients were included (mean age: 65 (inter-quartile range 52–79), male: 63%). Forty-one percent of patients demonstrated a vessel overlying percutaneous tracheostomy insertion sites (C6–T1); veins were more common than arteries (69%, p = 0.001). Males were more likely to display veins (78 vs. 53%, p < 0.001). Discussion A substantial proportion of patients exhibited pre-tracheal vessels. Front-of-neck ultrasonography has huge potential to identify these. Based on these data, we believe ultrasonography may be an effective screening tool for percutaneous tracheostomy procedures to reduce complications. Further research is required to study outcomes.
PROGRAMMING OF MAC SCHEME FOR STOKES EQUATIONS

In this notes, we summarize numerical methods for solving Stokes equations on rectangular grid, and solve it by multigrid vcycle method with distributive Gauss-Seidel relaxation as smoothing. The numerical methods we concerned are MAC scheme, nonconforming rotate bilinear FEM and nonconforming rotate bilinear FVM. 1. PROBLEM STATEMENT We consider Stokes equation (1.1) 8 >< >: μ ~ u +rp =~ f in ⌦, r · ~ u =0 in ⌦. ~ u =0 on @⌦ where ~ u = (u, v), and ~ f = (f1, f2). 2. MAC DISCRETIZATION
YAP 1 EXPRESSION PREDICTS SENSITIVITY TO DUAL AKT AND P 70 S 6 K INHIBITION IN OVARIAN AND UTERINE MALIGNANCIES By

Purpose: The PI3K/AKT/P70S6K pathway is an attractive therapeutic target in ovarian and uterine malignancies due to its high rate of dysregulation and key roles in tumor growth. Here, we examined the biological effects of MSC2363318A, which is a novel inhibitor of AKT1, AKT3, and P70S6K. Experimental Design: Orthotopic murine models of ovarian and uterine cancer were utilized to study the effect of MSC2363318A on survival and regression. Moreover, in vitro experiments (MTT, Western blot analysis, plasmid transfection, and reverse phase protein array [RPPA]) were carried out to characterize underlying mechanisms and potential biomarkers of response. Results: MSC2363318A decreased tumor growth and metastases in multiple murine orthotopic models of ovarian (SKOV3ip1, HeyA8, and Igrov1) and uterine (Hec1a) cancer and reduced proliferation (Ki67) and angiogenesis (CD31) indices and increased cell death (cleaved caspase-3) markers. Synergy between MSC2363318A and paclitaxel was observed in vitro in protected (IC50 ≥ 5 μM) cell lines. RPPA identified YAP1 as a candidate marker to predict cell lines that were most sensitive to MSC2363318A (R=0.675, p=0.0015). After establishment of a bevacizumab resistant
Anthropometry-based 24-h urinary creatinine excretion reference for Chinese children

To establish 24-h urinary creatinine excretion reference ranges based on anthropometry in healthy Chinese children, a cross-sectional survey was conducted using twice-sampled 24-h urine and anthropometric variables. Age- and sex-specific 24-h creatinine excretion reference ranges (crude and related to individual anthropometric variables) were derived. During October 2013 and May 2014, urine samples were collected. Anthropometric variables were measured in the first survey. Data of 710 children (377 boys and 333 girls) aged 8–13 years who completed the study were analyzed. No significant difference was observed in 24-h urine volumes between the two samples (median [interquartile range): 855.0 [600.0–1272.0) mL vs. 900.0 [660.0–1220.0) mL, P = 0.277). The mean 24-h urine creatinine excretion was regarded as representative of absolute daily creatinine excretion in children. Sex-specific, body-weight-adjusted creatinine excretion reference values were 15.3 mg/kg/day (0.1353 mmol/kg/day) for boys and 14.3 mg/kg/day (0.1264 mmol/kg/day) for girls. Differences were significant between boys and girls within the same age group but not across different age groups within the same sex. Ideal 24-h creatinine excretion values for height were derived for potential determination of the creatinine height index. These data can serve as reference ranges to calculate ratios of analyte to creatinine. The creatinine height index can be used to assess somatic protein status.
Telemedicine-Based Health Coaching Is Effective for Inducing Weight Loss and Improving Metabolic Markers.

BACKGROUND To assess the efficacy of health coaching (HC) delivered through videoconferencing (VC) to favorably change physical activity (PA), weight, and metabolic markers in adults with high body mass index (BMI). MATERIALS AND METHODS Thirty adults (BMI ≥30 kg/m2) were randomly assigned to one of three groups: VC, in-person (IP), or control group (CG). Participants received wireless watches and weight scales to sync with their personal smartphones; recorded data were wirelessly uploaded to a secure database. Participants assigned to VC and IP received individualized HC by a multidisciplinary team (registered dietitian, exercise physiologist, and medical doctor) based on data uploaded over the 12-week intervention. Steps/day and weight loss were analyzed through analyses of covariance. RESULTS Within- and between-group changes in weight (kg), glucose, insulin, hemoglobin A1c (HbA1c), and Homeostasis Model Assessment estimate of insulin resistance (HOMA-IR) were analyzed through analyses of variance. Weight loss was greater (p < 0.05) for VC (8.23 ± 4.5 kg; 7.7%) than IP (3.2 ± 2.6 kg; 3.4%) and CG (2.9 ± 3.9 kg; 3.3%), respectively. Steps/day were significantly higher in VC than IP at week 4 and VC was significantly higher than the CG at weeks 6, 8, 9, and 11 (p ≤ 0.05). No within- or between-group differences were found for glucose, insulin, or HbA1C. HOMA-IR decreased for VC only (p ≤ 0.05). CONCLUSIONS Our innovative, multidisciplinary, telemedicine HC delivered through VC led to more favorable changes in weight loss, PA (steps/day), and HOMA-IR than IP or no HC. VC may be an economical approach to improve health and promote behavior change in obese adults. CLINICAL TRIAL REGISTRATION NUMBER ClinicalTrials.gov identifier NCT03278951.
Density-dependent interspecific interactions and the complexity–stability relationship

Ever since May theorized that communities with larger numbers of species or interspecific interactions are inherently unstable, the mechanism allowing for the stable existence of complex communities in nature has been a central question in ecology. The main efforts to answer this question have sought to identify non-random features of ecological systems that can reverse a negative complexity–stability relationship into a positive one, but are far from successful, especially in their generality. Here, using the traditional community matrix analysis, we show that variation in the density dependence of interspecific interactions, which should be ubiquitous in nature, can dramatically affect the complexity–stability relationship. More specifically, we reveal that a positive complexity–stability relationship arises when harmful interspecific effects have larger density dependence than beneficial ones, regardless of the signs (i.e. positive or negative) of their dependence. Furthermore, numerical simulations demonstrated the synergistic stabilizing effect of interaction type diversity and density-dependence variation. Thus, this concept of density-dependence variation advances our understanding of the complexity–stability relationship in the real world.
Deep Learning with unsupervised data labeling for weeds detection on UAV images

In recent years, weeds is responsible for most of the agricultural yield losses. To deal with this threat, farmers resort to spraying pesticides throughout the field. Such method not only requires huge quantities of herbicides but impact environment and humans health. One way to reduce the cost and environmental impact is to allocate the right doses of herbicide at the right place and at the right time (Precision Agriculture). Nowadays, Unmanned Aerial Vehicle (UAV) is becoming an interesting acquisition system for weeds localization and management due to its ability to obtain the images of the entire agricultural field with a very high spatial resolution and at low cost. Despite the important advances in UAV acquisition systems, automatic weeds detection remains a challenging problem because of its strong similarity with the crops. Recently Deep Learning approach has shown impressive results in different complex classification problem. However, this approach needs a certain amount of training data but, creating large agricultural datasets with pixel-level annotations by expert is an extremely time consuming task. In this paper, we propose a novel fully automatic learning method using Convolutional Neuronal Networks (CNNs) with unsupervised training dataset collection for weeds detection from UAV images. The proposed method consists in three main phases. First we automatically detect the crop lines and using them to identify the interline weeds. In the second phase, interline weeds are used to constitute the training dataset. Finally, we performed CNNs on this dataset to build a model able to detect the crop and weeds in the images. The results obtained are comparable to the traditional supervised training data labeling. The accuracy gaps are 1.5% in the spinach field and 6% in the bean field.
3-HBP: A Three-Level Hidden Bayesian Link Prediction Model in Social Networks

In social networks, link establishment among the users is affected by complex factors. In this paper, we try to investigate the internal and external factors that affect the formation of links and propose a three-level hidden Bayesian link prediction model by integrating the user behavior as well as user relationships to link prediction. First, based on the user multiple interest characteristics, a latent Dirichlet allocation (LDA) traditional text modeling method is applied into user behavior modeling. Taking the advantage of LDA topic model in dealing with the problem of polysemy and synonym, we can mine user latent interest distribution and analyze the effects of internal driving factors. Second, owing to the power-law characteristics of user behavior, LDA is improved by Gaussian weighting. In this way, the negative impact of the interest distribution to the high-frequency users can be reduced and the expression ability of interests can be enhanced. Furthermore, taking the impact of common neighbor dependencies in link establishment, the model can be extended with hidden naive Bayesian algorithm. By quantifying the dependencies between common neighbors, we can analyze the effects of external driving factors and combine internal driving factors to link prediction. Experimental results indicate that the model can not only mine user latent interest distribution but also can improve the performance of link prediction effectively.
BCL2 Regulates Differentiation of Intestinal Fibroblasts.

Background Fibrosis in patients with Crohn's disease (CD) results from an imbalance toward excessive fibrous tissue formation driven by fibroblasts. Activation of fibroblasts is linked to the B-cell lymphoma 2 (BCL2) family, which is involved in the induction of apoptosis. We investigated the impact of BCL2 repression on fibrogenesis. Methods The model of dextran sodium sulfate (DSS)-induced chronic colitis and the heterotopic transplantation model of fibrosis were used. Following the administration of the BCL2 antagonist (ABT-737, 50 mg/kg/d), collagen layer thickness and hydroxyproline (HYP) content were determined. Fibroblasts were stimulated with the BCL2 antagonist (0.01-100 µM). BCL2, alpha smooth muscle actin (αSMA), and collagen I (COL1A1) were determined by quantitative polymerase chain reaction (qPCR), immunofluorescence microscopy (IF), and western blot (WB). mRNA expression pattern was determined by next-generation sequencing (NGS). Results Collagen layer thickness was significantly decreased in both DSS-induced chronic colitis and the transplantation model of fibrosis upon BCL2 antagonist administration compared with vehicle. Decreased HYP content confirmed the preventive effects of the BCL2 antagonist on fibrosis. In vitro, a significant increase in PI+/annexin V+ human colonic fibroblasts was determined by fluorescence-activated cell sorting upon treatment with high-dose BCL2 antagonist; at a lower dose, αSMA, COL1A1, and TGF were decreased. NGS, IF, and qPCR revealed decreased expression and nuclear translocation of GATA6 and SOX9, known for reprogramming fibroblasts. Conclusion BCL2 antagonist administration partially prevented fibrogenesis in both fibrosis models. The BCL2 antagonist reduced the expression of TGFβ-induced factors involved in differentiation of myofibroblasts, and therefore might represent a potential treatment option against CD-associated fibrosis.
HLTCOE Participation in TAC KBP 2017: Cold Start and EDL Pilot

The JHU HLTCOE participated in the Cold Start and the Entity Discovery and Linking tasks of the 2017 Text Analysis Conference Knowledge Base Population evaluation. For our sixth year of participation in Cold Start we continued our research with the KELVIN system. We submitted experimental variants that explore use of linking to Freebase across English and Chinese languages and add relations beyond those required by Cold Start. This is our third year of participation in Tri-lingual EDL and first year for the EDL Pilot for 10 Low-resource Languages. We used KELVIN in the Cold Start and Tri-lingual tasks and a new custom system for the Low-resource EDL task.
“Orphan” Connexin43 in Plakophilin-2 Deficient Hearts Revealed by Volume Electron Microscopy

Previous studies revealed an abundance of functional Connexin43 (Cx43) hemichannels consequent to loss of plakophilin-2 (PKP2) expression in adult murine hearts. The increased Cx43-mediated membrane permeability is likely responsible for excess entry of calcium into the cells, leading to an arrhythmogenic/cardiomyopathic phenotype. The latter has translational implications to the molecular mechanisms of inheritable arrhythmogenic right ventricular cardiomyopathy (ARVC). Despite functional evidence, visualization of these “orphan” (i.e., non-paired in a gap junction configuration) Cx43 hemichannels remains lacking. Immuno-electron microscopy (IEM) remains an extremely powerful tool to localize, with nanometric resolution, a protein within its native structural landscape. Yet, challenges for IEM are to preserve the antigenicity of the molecular target and to provide access for antibodies to reach their target, while maintaining the cellular/tissue ultrastructure. Fixation is important for maintaining cell structure, but strong fixation and vigorous dehydration (as it is routine for EM) can alter protein structure, thus impairing antigen-antibody binding. Here, we implemented a method to combine pre-embedding immunolabeling (pre-embedding) with serial block-face scanning electron microscopy (SBF-SEM). We utilized a murine model of cardiomyocyte-specific, Tamoxifen (TAM) activated knockout of PKP2. Adult hearts were harvested 14 days post-TAM, at this time hearts present a phenotype of concealed ARVC (i.e., an arrhythmogenic phenotype but no overt structural disease). Thick (200 µm) vibratome slices were immunolabelled for Cx43 and treated with nanogold or FluoroNanogold, coupled with a silver enhancement. Left or right ventricular free walls were dissected and three-dimensional (3D) localization of Cx43 in cardiac muscle was performed using SBF-SEM. Reconstructed images allowed us to visualize the entire length of gap junction plaques, seen as two parallel, closely packed strings of Cx43-immunoreactive beads at the intercalated disc. In contrast, in PKP2-deficient hearts we observed bulging of the intercellular space, and entire areas where only one of the two strings could be observed, indicating the presence of orphan Cx43. We conclude that pre-embedding and SBF-SEM allowed visualization of cardiac Cx43 plaques in their native environment, providing for the first time a visual complement of functional data indicating the presence of orphan Cx43 hemichannels resulting from loss of desmosomal integrity in the heart.
An in vitro and ex vivo Study on Antioxidant Activity of Coriander Seeds

The antioxidant activity of extracts of different polarity from seeds of Local variety of Coriandrum sativum was assessed via both in vitro and ex vivo models. Results indicate that hexane extract of coriander exhibited no appreciable affects at either of the concentrations in all the three in vitro free radical scavenging models i.e. hydroxyl radical, super oxide radical and nitric oxide radical. Instead, it showed prooxidant activity at higher concentrations. Whereas methanol: hexane extracts of coriander were found to be ineffective in quenching hydroxyl radical but revealed only moderate activity in quenching super oxide radical (EC50=711.81 μg/ml) and nitric oxide radical (EC50=569.02 μg/ml). Only methanolic extract of Local variety offered strong antioxidant activity in a concentration dependent manner for the same three free radicals with EC50 of 18.33 μg/ml, 553.50 μg/ml and 179.53 μg/ml respectively. Even in vitro linoleic acid peroxidation model proved methanolic extract of coriander (80% inhibition till 48 h) to be far better than standard antioxidant ascorbic acid (70% inhibition till 12 h). EC50 and SC50 for ex vivo linoleic acid peroxidation of rat liver homogenate and erythrocytes were recorded as 383.10 μg/ml and 166.78 μg/ml respectively. The methanolic extract of Local variety was further evaluated for its protective effect on osmotic fragility and antioxidant enzymes of erythrocytes at various time intervals (24–96 h). The decrease in% hemolysis and protection of activities of antioxidant enzymes even for 96 h of incubation in test groups supplemented with coriander proved indubitably, the effectiveness of methanolic coriander extract in alleviating protective mechanisms.