LLukas22/scidocs huggingface dataset:
Genomic selection using regularized linear regression models: ridge regression, lasso, elastic net and their extensions

BACKGROUND
Genomic selection (GS) is emerging as an efficient and cost-effective method for estimating breeding values using molecular markers distributed over the entire genome. In essence, it involves estimating the simultaneous effects of all genes or chromosomal segments and combining the estimates to predict the total genomic breeding value (GEBV). Accurate prediction of GEBVs is a central and recurring challenge in plant and animal breeding. The existence of a bewildering array of approaches for predicting breeding values using markers underscores the importance of identifying approaches able to efficiently and accurately predict breeding values. Here, we comparatively evaluate the predictive performance of six regularized linear regression methods-- ridge regression, ridge regression BLUP, lasso, adaptive lasso, elastic net and adaptive elastic net-- for predicting GEBV using dense SNP markers.


METHODS
We predicted GEBVs for a quantitative trait using a dataset on 3000 progenies of 20 sires and 200 dams and an accompanying genome consisting of five chromosomes with 9990 biallelic SNP-marker loci simulated for the QTL-MAS 2011 workshop. We applied all the six methods that use penalty-based (regularization) shrinkage to handle datasets with far more predictors than observations. The lasso, elastic net and their adaptive extensions further possess the desirable property that they simultaneously select relevant predictive markers and optimally estimate their effects. The regression models were trained with a subset of 2000 phenotyped and genotyped individuals and used to predict GEBVs for the remaining 1000 progenies without phenotypes. Predictive accuracy was assessed using the root mean squared error, the Pearson correlation between predicted GEBVs and (1) the true genomic value (TGV), (2) the true breeding value (TBV) and (3) the simulated phenotypic values based on fivefold cross-validation (CV).


RESULTS
The elastic net, lasso, adaptive lasso and the adaptive elastic net all had similar accuracies but outperformed ridge regression and ridge regression BLUP in terms of the Pearson correlation between predicted GEBVs and the true genomic value as well as the root mean squared error. The performance of RR-BLUP was also somewhat better than that of ridge regression. This pattern was replicated by the Pearson correlation between predicted GEBVs and the true breeding values (TBV) and the root mean squared error calculated with respect to TBV, except that accuracy was lower for all models, most especially for the adaptive elastic net. The correlation between the predicted GEBV and simulated phenotypic values based on the fivefold CV also revealed a similar pattern except that the adaptive elastic net had lower accuracy than both the ridge regression methods.


CONCLUSIONS
All the six models had relatively high prediction accuracies for the simulated data set. Accuracy was higher for the lasso type methods than for ridge regression and ridge regression BLUP.
Asymmetric spiders: Supplier heterogeneity and the organization of firms

We consider a property rights model of a firm with two heterogeneous suppliers. The headquarters determine the firm’s organizational structure, and we analyze which sourcing mode (outsourcing or vertical integration) is chosen for which of the asymmetric inputs. If suppliers’ investment choices are strategic complements, the firm may keep the technologically more important input inside its boundaries and outsource the less important supplier. The firm also tends to keep more sophisticated inputs in-house, while choosing an external supplier organization for simpler and for low-cost components. These theoretical predictions are consistent with numerous case studies and recent empirical evidence on the internal organization of firms. JEL-Classification: D23, L23, F23
The CHOLEGAS study: multicentric randomized, blinded, controlled trial of gastrectomy plus prophylactic cholecystectomy versus gastrectomy only, in adults submitted to Gastric cancer surgery with curative intent

BACKGROUND
The incidence of gallstones and gallbladder sludge is known to be higher in patients after gastrectomy than in general population. This higher incidence is probably related to surgical dissection of the vagus nerve branches and the anatomical gastrointestinal reconstruction. Therefore, some surgeons perform routine concomitant cholecystectomy during standard surgery for gastric malignancies. However, not all the patients who are diagnosed to have cholelithiasis after gastric cancer surgery will develop symptoms or require additional surgical treatments and a standard laparoscopic cholecystectomy is feasible even in those patients who underwent previous gastric surgery. At the present, no randomized study has been published and the decision of gallbladder management is left to each surgeon preference.


DESIGN
The study is a randomized controlled investigation. The study will be performed in the General and Oncologic Surgery, Department of Oncology-Azienda Ospedaliero-Universitaria Careggi-Florence-Italy, a large teaching institution, with the participation of all surgeons who accept to be involved in, together with other Italian Surgical Centers, on behalf of the GIRCG (Italian Research Group for Gastric Cancer).The patients will be randomized into two groups: in the first group the patient will be submitted to prophylactic cholecystectomy during standard surgery for curable gastric cancer (subtotal or total gastrectomy), while in the second group he/she will be submitted to standard gastric surgery only.


TRIAL REGISTRATION
ClinicalTrials.gov ID. NCT00757640.
A comparison of the clinical effectiveness and costs of mental health nurse supplementary prescribing and independent medical prescribing: a post-test control group study

BACKGROUND
Supplementary prescribing for mental health nurses was first introduced in the UK in 2003. Since then, a number of studies have reported stakeholders' perceptions of the success of the initiative. However, there has been little experimental research conducted into its effectiveness. This paper reports findings from the first known study to compare the cost and clinical impact of mental health nurse supplementary prescribing to independent medical prescribing.


METHODS
A post-test control group experimental design was used to compare the treatment costs, clinical outcomes and satisfaction of patients in receipt of mental health nurse supplementary prescribing with a matched group of patients in receipt of independent prescribing from consultant psychiatrists. The sample comprised 45 patients in receipt of mental health nurse supplementary prescribing for a minimum of six months and a matched group (by age, gender, diagnosis, and chronicity) of patients prescribed for by psychiatrists.


RESULTS
There were no significant differences between patients in the nurse supplementary prescribers' group and the independent prescribers' group in terms of medication adherence, health status, side effects, and satisfaction with overall care. Total costs per patient for service use were 803 pounds higher for the nurse prescribers' group but this difference was not significant (95% confidence interval--1341 pounds to 3020 pounds).


CONCLUSIONS
No significant differences were found between the health and social outcomes of patients in the mental health nurse supplementary prescribers' group, and those prescribed for by the independent medical prescribers. The cost appraisal also showed that there was no significant difference in the costs of the two types of prescribing, although the pattern of resources used differed between patients in the two prescriber groups. The results suggest that mental health nurse supplementary prescribers can deliver similar health benefits to patients as consultant psychiatrists without any significant difference in patients' service utilisation costs.
Perspectives on mock modular forms

Article history: Received 30 August 2016 Received in revised form 2 February 2017 Accepted 20 February 2017 Available online 24 February 2017 Communicated by D. Goss
A Stochastic View of Optimal Regret through Minimax Duality

We study the regret of optimal strategies for online convex optimization games. Using von Neumann’s minimax theorem, we show that the optimal regret in this adversarial setting is closely related to the behavior of the empirical minimization algorithm in a stochastic process setting: it is equal to the maximum, over joint distributions of the adversary’s action sequence, of the difference between a sum of minimal expected losses and the minimal empirical loss. We show that the optimal regret has a natural geometric interpretation, since it can be viewed as the gap in Jensen’s inequality for a concave functional—the minimizer over the player’s actions of expected loss—defined on a set of probability distributions. We use this expression to obtain upper and lower bounds on the regret of an optimal strategy for a variety of online learning problems. Our method provides upper bounds without the need to construct a learning algorithm; the lower bounds provide explicit optimal strategies for the adversary.
The blood-brain barrier: an important concept in neuroimaging.

Many of the modern techniques for brain imaging such as enhanced computed tomography (CT), enhanced magnetic resonance (MR) imaging, single-photon emission CT, and positron emission tomography rely on the presence or absence of a normal blood-brain barrier (BBB). Other techniques such as cerebral angiography, may have a direct effect on the BBB. We shall review the anatomy and physiology of the BBB to provide essential background information for neuroradiologists.
Improved Garbled Circuit: Free XOR Gates and Applications

We present a new garbled circuit construction for two-party secure function evaluation (SFE). In our one-round protocol, XOR gates are evaluated “for free”, which results in the corresponding improvement over the best garbled circuit implementations (e.g. Fairplay [19]). We build permutation networks [26] and Universal Circuits (UC) [25] almost exclusively of XOR gates; this results in a factor of up to 4 improvement (in both computation and communication) of their SFE. We also improve integer addition and equality testing by factor of up to 2. We rely on the Random Oracle (RO) assumption. Our constructions are proven secure in the semi-honest model.
A hybrid artificial intelligence model for river flow forecasting

A hybrid hydrologic estimation model is presented with the aim of performing accurate river flow forecasts without the need of using prior knowledge from the experts in the field. The problem of predicting stream flows is a non-trivial task because the various physical mechanisms governing the river flow dynamics act on a wide range of temporal and spatial scales and almost all the mechanisms involved in the river flow process present some degree of nonlinearity. The proposed system incorporates both statistical and artificial intelligence techniques used at different stages of the reasoning cycle in order to calculate the mean daily water volume forecast of the Salvajina reservoir inflow located at the Department of Cauca, Colombia. The accuracy of the proposed model is compared against other well-known artificial intelligence techniques and several statistical tools previously applied in time series forecasting. The results obtained from the experiments carried out using real data from years 1950 to 2006 demonstrate the superiority of the hybrid system. © 2013 Elsevier B.V. All rights reserved.
The relationship between gamma-glutamyltransferase and coronary collateral circulation in patients with chronic total occlusion.

OBJECTIVE
The aim of this study was to evaluate the relation between blood gamma-glutamyltransferase (GGT) levels and coronary collateral circulation in patients with chronic total occlusion (CTO).


METHODS
Two hundred twenty-two patients with chronic stable coronary artery disease (CAD) and CTO were included in this cross-sectional, observational study. Coronary collaterals were graded from 0 to 3 according to the Rentrop method. Patients with grade 0-1 collateral development were regarded as poor collateral group (n=66) while patients with grade 2-3 collateral development were regarded as good collateral group (n=156). Statistical analysis was performed using independent samples t, Mann-Whitney U and Chi-square tests, logistic regression and receiver operator curve analysis.


RESULTS
The poor coronary collateral group had significantly higher levels of serum GGT compared to the good collateral group (p<0.001). Multiple logistic regression analysis showed that GGT levels were independent predictors of poor collateral circulation (OR-0.946, 95% CI=0.918-0.9719, p<0.001). The result of ROC curve analysis for GGT was as following: area under the ROC curve (AUC)=0.732, 95% CI: 0.622-0.841, p<0.001.


CONCLUSION
Higher GGT levels are associated with poor coronary collateral circulation in patients with CTO. GGT may be used to predict the grade of coronary collateral circulation in CTO patients with chronic stable CAD.
Face Verification via Class Sparsity Based Supervised Encoding

Autoencoders are deep learning architectures that learn feature representation by minimizing the reconstruction error. Using an autoencoder as baseline, this paper presents a novel formulation for a class sparsity based supervised encoder, termed as CSSE. We postulate that features from the same class will have a common sparsity pattern/support in the latent space. Therefore, in the formulation of the autoencoder, a supervision penalty is introduced as a joint-sparsity promoting <inline-formula><tex-math notation="LaTeX">$l_{2,1}$</tex-math><alternatives> <inline-graphic xlink:href="vatsa-ieq1-2569436.gif"/></alternatives></inline-formula>-norm. The formulation of CSSE is derived for a single hidden layer and it is applied for multiple hidden layers using a greedy layer-by-layer learning approach. The proposed CSSE approach is applied for learning face representation and verification experiments are performed on the LFW and PaSC face databases. The experiments show that the proposed approach yields improved results compared to autoencoders and comparable results with state-of-the-art face recognition algorithms.
Software Test Data Generation using Ant Colony Optimization

State-based testing is frequently used in software testing. Test data generation is one of the key issues in software testing. A properly generated test suite may not only locate the errors in a software system, but also help in reducing the high cost associated with software testing. It is often desired that test data in the form of test sequences within a test suite can be automatically generated to achieve required test coverage. This paper proposes an Ant Colony Optimization approach to test data generation for the state-based software testing. Keywords— Software testing, ant colony optimization, UML.
Computational Exploration of Metaphor Comprehension Processes Using a Semantic Space Model

Recent metaphor research has revealed that metaphor comprehension involves both categorization and comparison processes. This finding has triggered the following central question: Which property determines the choice between these two processes for metaphor comprehension? Three competing views have been proposed to answer this question: the conventionality view (Bowdle & Gentner, 2005), aptness view (Glucksberg & Haught, 2006b), and interpretive diversity view (Utsumi, 2007); these views, respectively, argue that vehicle conventionality, metaphor aptness, and interpretive diversity determine the choice between the categorization and comparison processes. This article attempts to answer the question regarding which views are plausible by using cognitive modeling and computer simulation based on a semantic space model. In the simulation experiment, categorization and comparison processes are modeled in a semantic space constructed by latent semantic analysis. These two models receive word vectors for the constituent words of a metaphor and compute a vector for the metaphorical meaning. The resulting vectors can be evaluated according to the degree to which they mimic the human interpretation of the same metaphor; the maximum likelihood estimation determines which of the two models better explains the human interpretation. The result of the model selection is then predicted by three metaphor properties (i.e., vehicle conventionality, aptness, and interpretive diversity) to test the three views. The simulation experiment for Japanese metaphors demonstrates that both interpretive diversity and vehicle conventionality affect the choice between the two processes. On the other hand, it is found that metaphor aptness does not affect this choice. This result can be treated as computational evidence supporting the interpretive diversity and conventionality views.
Chlamydia and Gonorrhea in HIV-Infected Pregnant Women and Infant HIV Transmission.

BACKGROUND
Sexually transmitted infections (STIs) such as Chlamydia trachomatis (CT) and Neisseria gonorrhoeae (NG) can lead to adverse pregnancy and neonatal outcomes. The prevalence of STIs and its association with HIV mother-to-child transmission (MTCT) were evaluated in a substudy analysis from a randomized, multicenter clinical trial.


METHODOLOGY
Urine samples from HIV-infected pregnant women collected at the time of labor and delivery were tested using polymerase chain reaction testing for the detection of CT and NG (Xpert CT/NG; Cepheid, Sunnyvale, CA). Infant HIV infection was determined by HIV DNA polymerase chain reaction at 3 months.


RESULTS
Of the 1373 urine specimens, 249 (18.1%) were positive for CT and 63 (4.6%) for NG; 35 (2.5%) had both CT and NG detected. Among 117 cases of HIV MTCT (8.5% transmission), the lowest transmission rate occurred among infants born to CT- and NG-uninfected mothers (8.1%) as compared with those infected with only CT (10.7%) and both CT and NG (14.3%; P = 0.04). Infants born to CT-infected mothers had almost a 1.5-fold increased risk for HIV acquisition (odds ratio, 1.47; 95% confidence interval, 0.9-2.3; P = 0.09).


CONCLUSIONS
This cohort of HIV-infected pregnant women is at high risk for infection with CT and NG. Analysis suggests that STIs may predispose to an increased HIV MTCT risk in this high-risk cohort of HIV-infected women.
Compositional and microstructural characterization of thin film lead zirconate titanate ferroelectrics

Abstract Recent interest in thin film lead zirconate titanate (PZT) ferroelectrics has been intensified by the possible applications of these materials to non-volatile random access memory devices. In general, these thin films have different properties when compared with bulk ceramics of the same composition (Zr:Ti ranging from 48:52 to 30:70). We have begun investigating the composition and microstructure of sputtered submicron PZT films via electron probe microanalysis (EPMA), scanning electron microscopy (SEM) and transmission electron microscopy (TEM). Bulk analysis of various films (EPMA) shows reasonable agreement with the composition of the target (especially Zr:Ti ratios). SEM illustrates a variety of microstructures which primarily depend on target material, sputtering conditions and substrate morphology. Plan-view TEM has been used to investigate the grain orientation and morphology of the ferroelectric films. Grain size for PZT varies considerably from tens of nanometers to several hundred nanometers. The grain size depends on the composition of the films and the sputtering conditions. Cross-sectional TEM samples are being studied to determine the degree of abruptness of the various heterointerfaces in a device structure.
Wetlands as large-scale nature-based solutions: Status and challenges for research, engineering and management

Wetlands are often considered as nature-based solutions that can provide a multitude of services of great social, economic and environmental value to humankind. Changes in land-use, water-use and climate can all impact wetland functions and services. These changes occur at scales extending well beyond the local scale of an individual wetland. However, in practical applications, engineering and management decisions usually focus on individual wetland projects and local site conditions. Here, we systematically investigate if and to what extent research has addressed the large-scale dynamics of landscape systems with multiple wetlands, hereafter referred to as wetlandscapes, which are likely to be relevant for understanding impacts of regional to global change. Although knowledge in many cases is still limited, evidence suggests that the aggregated effects of multiple wetlands in the landscape can differ considerably from the functions observed at individual wetland scales. This applies to provisioning of ecosystem services such as coastal protection, biodiversity support, groundwater level and soil moisture regulation, flood regulation and contaminant retention. We show that parallel and circular flow-paths, through which wetlands are interconnected in the landscape, may largely control such scale-function differences. We suggest ways forward for addressing the mismatch between the scales at which changes take place and the scale at which observations and implementation are currently made. These suggestions can help bridge gaps between researchers and engineers, which is critical for improving wetland function-effect predictability and management. © 2017 The Author(s). Published by Elsevier B.V. This is an open access article under the CC
Management of biochemical recurrence after primary treatment of prostate cancer: a systematic review of the literature.

CONTEXT
Despite excellent cancer control with the treatment of localized prostate cancer (PCa), some men will experience a recurrence of disease. The optimal management of recurrent disease remains uncertain.


OBJECTIVE
To systematically review recent literature regarding management of biochemical recurrence after primary treatment for localized PCa.


EVIDENCE ACQUISITION
A comprehensive systematic review of the literature was performed from 2000 to 2012 to identify articles pertaining to management after recurrent PCa. Search terms included prostate cancer recurrence, salvage therapy, radiorecurrent prostate cancer, post HIFU, post cryoablation, postradiation, and postprostatectomy salvage. Studies were selected according to Preferred Reporting Items for Systematic Reviews and Meta-analysis (PRISMA) guidelines and required to provide a comprehensive description of primary and secondary treatments along with outcomes.


EVIDENCE SYNTHESIS
The data from 32 original publications were reviewed. The most common option for local salvage therapy after radical prostatectomy (RP) was radiation. Options for local salvage therapy after primary radiation included RP, brachytherapy, and cryotherapy. Different definitions of recurrence and risk profiles among patients make comparative assessment among salvage treatment modalities difficult. Triggers for intervention and factors predicting response to salvage therapy vary.


CONCLUSIONS
Radiation therapy (RT) after RP can provide durable prostate-specific antigen (PSA) responses in a sizeable percentage of men, especially when given early (ie, PSA <1 ng/ml). Though a few studies suggest improvements in mortality, prospective randomized trials are needed and underway. The role of salvage treatment after RT is less clear.