LLukas22/scidocs huggingface dataset:
Golimumab 3-year safety update: an analysis of pooled data from the long-term extensions of randomised, double-blind, placebo-controlled trials conducted in patients with rheumatoid arthritis, psoriatic arthritis or ankylosing spondylitis

OBJECTIVE
To assess pooled golimumab safety up to year 3 of rheumatoid arthritis (RA), psoriatic arthritis (PsA) and ankylosing spondylitis (AS) trials.


METHODS
Golimumab 50 and 100 mg, administered subcutaneously (SC) every 4 weeks (q4wk), were assessed in patients with active RA (methotrexate-naïve, methotrexate-experienced and anti-TNF (tumour necrosis factor)-experienced), PsA or AS, despite conventional therapy. Placebo control continued up to week (wk) 24 (wk 52, methotrexate-naïve), with early escape at wk 16 (wk 28, methotrexate-naïve); subsequently, all patients received golimumab 50 or 100 mg q4wk. After the blinded controlled period, golimumab doses could be adjusted per investigator discretion. Pooled safety analyses reported herein include data from placebo-controlled and uncontrolled study periods up to wk 160. Determinations of incidences/100 patient-years (pt-yrs) for rare events also included RA patients from a phase IIb trial.


RESULTS
Across five phase III trials of SC golimumab, 639 patients received placebo and 2226 received golimumab 50 mg (n=1249) and/or 100 mg (n=1501) up to wk 160 (patients may be included in more than one group because non-responders were allowed early escape); 1179 patients were treated for ≥156 weeks. For placebo, golimumab 50 mg and golimumab 100 mg, respective adverse event incidences/100 pt-yrs (95% CIs) up to wk 160 were: 0.28 (0.01 to 1.56), 0.30 (0.12 to 0.62), 0.41 (0.23 to 0.69) for death; 5.31 (3.20 to 8.30), 3.03 (2.36 to 3.82), 5.09 (4.36 to 5.90) for serious infection; 0.00 (0.00 to 0.84), 0.17 (0.05 to 0.44), 0.35 (0.18 to 0.62) for tuberculosis; 0.00 (0.00 to 0.84), 0.13 (0.03 to 0.38), 0.24 (0.10 to 0.46) for opportunistic infection; 0.00 (0.00 to 0.84), 0.00 (0.00 to 0.13), 0.12 (0.03 to 0.30) for demyelination; and 0.00 (0.00 to 0.84), 0.04 (0.00 to 0.24), 0.18 (0.06 to 0.38) for lymphoma.


CONCLUSIONS
SC golimumab safety up to 3 years remained consistent with that of other TNF antagonists. Golimumab 100 mg showed numerically higher incidences of serious infections, demyelinating events and lymphoma than 50 mg; safety follow-up up to year 5 continues.
A Simple Method for Commonsense Reasoning

Commonsense reasoning is a long-standing challenge for deep learning. For example, it is difficult to use neural networks to tackle the Winograd Schema dataset [1]. In this paper, we present a simple method for commonsense reasoning with neural networks, using unsupervised learning. Key to our method is the use of language models, trained on a massive amount of unlabled data, to score multiple choice questions posed by commonsense reasoning tests. On both Pronoun Disambiguation and Winograd Schema challenges, our models outperform previous state-of-the-art methods by a large margin, without using expensive annotated knowledge bases or hand-engineered features. We train an array of large RNN language models that operate at word or character level on LM-1-Billion, CommonCrawl, SQuAD, Gutenberg Books, and a customized corpus for this task and show that diversity of training data plays an important role in test performance. Further analysis also shows that our system successfully discovers important features of the context that decide the correct answer, indicating a good grasp of commonsense knowledge.
Risk of diagnosed fractures in children with inflammatory bowel diseases.

BACKGROUND
Decreased bone mass is common in children with inflammatory bowel disease (IBD); however, fracture risk is unknown. We sought to evaluate fracture risk in children with IBD as compared to unaffected controls and determine whether this risk is affected by geographical region (a proxy for sun/vitamin D exposure) and oral steroid use.


METHODS
We identified cases of Crohn's disease (CD) and ulcerative colitis (UC), less than 20 years of age, using administrative data from 87 health plans. Each case was matched to three controls on the basis of age, gender, and geographical region. We identified fractures in cases and controls using ICD-9 diagnosis codes and measured oral steroid exposure using NDC codes.


RESULTS
The study included 733 children with CD, 488 with UC, and 3287 controls (mean age 15 years). IBD was not associated with a higher risk of fracture at any site (CD odds ratio [OR] 0.8, 95% confidence interval [CI] 0.6-1.1; UC OR 1.4, 95% CI 1.0-2.1) or at multiple sites (CD OR 0.8, 95% CI 0.4-1.7; UC OR 0.4, 95% CI 0.1-1.4). Among IBD patients we did not identify any significant differences in the fracture rate between those residing in the Northeast/Midwest versus the South (OR 1.3, 95% CI 0.8-2.2). Steroid exposure was not associated with the occurrence of fractures (P = 0.6).


CONCLUSIONS
Children with IBD are no more likely to have experienced a diagnosed fracture than age-, sex-, and gender-matched controls.
On Data Clustering Analysis: Scalability, Constraints, and Validation

Clustering is the problem of grouping data based on similarity. While this problem has attracted the attention of many researchers for many years, we are witnessing a resurgence of interest in new clustering techniques. In this paper we discuss some very recent clustering approaches and recount our experience with some of these algorithms. We also present the problem of clustering in the presence of constraints and discuss the issue of clustering validation.
Who Makes Trends? Understanding Demographic Biases in Crowdsourced Recommendations

Users of social media sites like Facebook and Twitter rely on crowdsourced content recommendation systems (e.g., Trending Topics) to retrieve important and useful information.
Passive Inference of User Actions through IoT Gateway Encrypted Traffic Analysis

Internet of Things (IoT) devices become widely used and their control is often provided through a cloud-based web service that interacts with an IoT gateway, in particular for individual users and home automation.In this paper, we propose a technique to infer private user information, i.e., actions performed, by considering a vantage point outside the end-user local IoT network. By learning the relationships between the user actions and the traffic sent by the web service to the gateway, we have been able to establish elementary signatures, one for each possible action, which can be then composed to discover compound actions in encrypted traffic.We evaluated the efficiency of our approach on one IoT gateway interacting with up to 16 IoT devices and showed that a passive attacker can infer user activities with an accuracy above 90%.
Challenges Women with Disability Face in Accessing and Using Maternal Healthcare Services in Ghana: A Qualitative Study

BACKGROUND
While a number of studies have examined the factors affecting accessibility to and utilisation of healthcare services by persons with disability in general, there is little evidence about disabled women's access to maternal health services in low-income countries and few studies consult disabled women themselves to understand their experience of care and the challenges they face in accessing skilled maternal health services. The objective of this paper is to explore the challenges women with disabilities encounter in accessing and using institutional maternal healthcare services in Ghana.


METHODS AND FINDINGS
A qualitative study was conducted in 27 rural and urban communities in the Bosomtwe and Central Gonja districts of Ghana with a total of 72 purposively sampled women with different physical, visual, and hearing impairments who were either lactating or pregnant at the time of this research. Semi-structured in-depth interviews were used to gather data. Attride-Stirling's thematic network framework was used to analyse the data. Findings suggest that although women with disability do want to receive institutional maternal healthcare, their disability often made it difficult for such women to travel to access skilled care, as well as gain access to unfriendly physical health infrastructure. Other related access challenges include: healthcare providers' insensitivity and lack of knowledge about the maternity care needs of women with disability, negative attitudes of service providers, the perception from able-bodied persons that women with disability should be asexual, and health information that lacks specificity in terms of addressing the special maternity care needs of women with disability.


CONCLUSIONS
Maternal healthcare services that are designed to address the needs of able-bodied women might lack the flexibility and responsiveness to meet the special maternity care needs of women with disability. More disability-related cultural competence and patient-centred training for healthcare providers as well as the provision of disability-friendly transport and healthcare facilities and services are needed.
End-to-End Instance Segmentation with Recurrent Attention

While convolutional neural networks have gained impressive success recently in solving structured prediction problems such as semantic segmentation, it remains a challenge to differentiate individual object instances in the scene. Instance segmentation is very important in a variety of applications, such as autonomous driving, image captioning, and visual question answering. Techniques that combine large graphical models with low-level vision have been proposed to address this problem, however, we propose an end-to-end recurrent neural network (RNN) architecture with an attention mechanism to model a human-like counting process, and produce detailed instance segmentations. The network is jointly trained to sequentially produce regions of interest as well as a dominant object segmentation within each region. The proposed model achieves competitive results on the CVPPP [27], KITTI [12], and Cityscapes [8] datasets.
Comparison of short tandem repeat and variable number tandem repeat genetic markers for quantitative determination of allogeneic bone marrow transplant engraftment

Variable number tandem repeats (VNTRs) were among the first genetic markers used to quantitate bone marrow transplant engraftment. The limitations of PCR-based VNTR markers in distinguishing some donor/recipient pairs has shown the need for additional genetic markers to analyze engraftment. Short tandem repeats (STRs) provide an excellent tool for this purpose because of their high degree of polymorphism and relatively short length. We compared STR analysis results with previous VNTR results for 16 post-transplantation samples from four allogeneic bone marrow transplant patients. Previously analyzed patient samples were chosen to cover the full range of engraftment. DNA samples from each patient were analyzed in a blinded fashion. Good quantitative correlation was found between STR and VNTR results in samples from all four patients. STR markers were informative in one patient for whom PCR-based VNTR markers were not available. Correlation of VNTR and STR methods helps to validate the use of STRs for the quantitative analysis of bone marrow transplant engraftment. This study demonstrates that STR-based human identity testing kits are well suited for engraftment analysis.Bone Marrow Transplantation (2002) 29, 243–248. doi:10.1038/sj.bmt.1703360
A survey of some problems in sterilization.

some glaring examples of breakdown in sterilization (Savage, 1944; Walter, 1948; Howie and Timbury, 1956; Bowie 1955, 1957). More recently, stimulated by the original observations, administrators and hospital authorities are becoming increasingly conscious that the whole machinery of sterilization in hospitals needs a drastic overhaul (Nuffield Provincial Hospitals Trust, 1958; Medical Research Council Working Party's Report, 1959). At the same time many new techniques and methods are becoming available. Rival claims are made for different methods and it is important to keep some sense of perspective and to decide for what purposes different methods of sterilization are most suitable. The aim of this article is to assess the present situation, to outline some of the main problems, and to suggest some of the lines along which development is likely to proceed in the immediate and in the
Skin Segmentation Using YUV and RGB Color Spaces

Skin detection is used in many applications, such as face recognition, hand tracking, and human-computer interaction. There are many skin color detection algorithms that are used to extract human skin color regions that are based on the thresholding technique since it is simple and fast for computation. The efficiency of each color space depends on its robustness to the change in lighting and the ability to distinguish skin color pixels in images that have a complex background. For more accurate skin detection, we are proposing a new threshold based on RGB and YUV color spaces. The proposed approach starts by converting the RGB color space to the YUV color model. Then it separates the Y channel, which represents the intensity of the color model from the U and V channels to eliminate the effects of luminance. After that the threshold values are selected based on the testing of the boundary of skin colors with the help of the color histogram. Finally, the threshold was applied to the input image to extract skin parts. The detected skin regions were quantitatively compared to the actual skin parts in the input images to measure the accuracy and to compare the results of our threshold to the results of other’s thresholds to prove the efficiency of our approach. The results of the experiment show that the proposed threshold is more robust in terms of dealing with the complex background and light conditions than others. Keyword: Skin segmentation; Thresholding technique; Skin detection; Color space
Paper Series Social Security in Theory and Practice With Implications for Reform

166 countries have some kind of public old age pension. What economic forces create and sustain old-age Social Security as a public program? In the first part of the paper, we document some of the internationally and historically common features of Social Security programs including explicit and implicit taxes on labor supply, pay-as-you-go features, intergenerational redistribution, benefits which are increasing functions of lifetime earnings and not means-tested. The rest of the paper discusses various positive theories of Social Security and compares each of them with the empirical regularities uncovered in the first part. We partition theories into three groups: “political”, “efficiency” and “narrative” theories. We explore three political theories: the majority rational voting model (with its two versions: “the elderly as the leaders of a winning coalition with the poor” and the “once and for all election” model), the “time-intensive model of political competition” and the “taxpayer protection model”. We then discuss the “efficiency theories,” which view creation of the SS program as a full or partial solution to some market failure. Efficiency explanations of social security include the “SS as welfare for the elderly”, the “retirement increases productivity to optimally manage human capital externalities”, “optimal retirement insurance”, “labor market congestion,” the “prodigal father problem”, the “misguided Keynesian”, the “optimal longevity insurance”, the “government economizing transaction costs”, and the “return on human capital investment” theory. Finally we analyze three “narrative” theories of social security: the “chain letter theory”, the “monopoly capitalism theory”, and the “Sub-but-Nearly-Optimal policy response to private pensions theory”. The political and efficiency explanations are compared with the international and historical facts and used to derive implications for replacing the typical pay-as-you-go system with a forced savings plan. Most of the explanations suggest that forced savings does not increase welfare. In fact, it may decrease it.
Challenges in representation learning: A report on three machine learning contests

The ICML 2013 Workshop on Challenges in Representation Learning(1) focused on three challenges: the black box learning challenge, the facial expression recognition challenge, and the multimodal learning challenge. We describe the datasets created for these challenges and summarize the results of the competitions. We provide suggestions for organizers of future challenges and some comments on what kind of knowledge can be gained from machine learning competitions.
Example-dependent cost-sensitive decision trees

Several real-world classification problems are example-dependent cost-sensitive in nature, where the costs due to misclassification vary between examples. However, standard classification methods do not take these costs into account, and assume a constant cost of misclassification errors. State-of-the-art example-dependent cost-sensitive techniques only introduce the cost to the algorithm, either before or after training, therefore, leaving opportunities to investigate the potential impact of algorithms that take into account the real financial example-dependent costs during an algorithm training. In this paper, we propose an example-dependent cost-sensitive decision tree algorithm, by incorporating the different example-dependent costs into a new cost-based impurity measure and a new cost-based pruning criteria. Then, using three different databases, from three real-world applications: credit card fraud detection, credit scoring and direct marketing, we evaluate the proposed method. The results show that the proposed algorithm is the best performing method for all databases. Furthermore, when compared against a standard decision tree, our method builds significantly smaller trees in only a fifth of the time, while having a superior performance measured by cost savings, leading to a method that not only has more business-oriented results, but also a method that creates simpler models that are easier to analyze. 2015 Elsevier Ltd. All rights reserved.
Voxel-based analysis of 11C-PIB scans for diagnosing Alzheimer's disease.

UNLABELLED
The positron emission tomography (PET) radioligand N-methyl-11C-2-(4-methylaminophenyl)-6-hydroxybenzothiazole (also known as 11C-6-OH-BTA-1 or 11C-PIB) binds to amyloid-beta (Abeta), which accumulates pathologically in Alzheimer's disease (AD). Although 11C-PIB accumulation is greater in patients with AD than in healthy controls at a group level, the optimal method for discriminating between these 2 groups has, to our knowledge, not been established. We assessed the use of data-determined standardized voxels of interest (VOIs) to improve the classification capability of 11C-PIB scans on patients with AD.


METHODS
A total of 16 controls and 14 AD age-matched patients were recruited. All subjects underwent a 11C-PIB scan and structural MRI. Binding potential (a measure of amyloid burden) was calculated for each voxel using the Logan graphical method with cerebellar gray matter as the reference region. Voxel maps were then partial-volume corrected and spatially normalized by MRI onto a standardized template. The subjects were divided into 2 cohorts. The first cohort (control, 12; AD, 9) was used for statistical parametric mapping analysis and delineation of data-based VOIs. These VOIs were tested in the second cohort (control, 4; AD, 5) of subjects.


RESULTS
Statistical parametric mapping analysis revealed significant differences between control and AD groups. The VOI map determined from the first cohort resulted in complete separation between the control and the AD subjects in the second cohort (P < 0.02). Binding potential values based on this VOI were in the same range as other reported individual and mean cortical VOI results.


CONCLUSION
A standardized VOI template that is optimized for control or AD group discrimination provides excellent separation of control and AD subjects on the basis of 11C-PIB uptake. This VOI template can serve as a potential replacement for manual VOI delineation and can eventually be fully automated, facilitating potential use in a clinical setting. To facilitate independent analysis and validation with more and a broader variety of subjects, this VOI template and the software for processing will be made available through the Internet.
Protection motivation and deterrence: a framework for security policy compliance in organisations

Received: 21 February 2008 Revised: 15 August 2008 2nd Revision: 31 January 2009 Accepted: 23 February 2009 Abstract Enterprises establish computer security policies to ensure the security of information resources; however, if employees and end-users of organisational information systems (IS) are not keen or are unwilling to follow security policies, then these efforts are in vain. Our study is informed by the literature on IS adoption, protection-motivation theory, deterrence theory, and organisational behaviour, and is motivated by the fundamental premise that the adoption of information security practices and policies is affected by organisational, environmental, and behavioural factors. We develop an Integrated Protection Motivation and Deterrence model of security policy compliance under the umbrella of Taylor-Todd’s Decomposed Theory of Planned Behaviour. Furthermore, we evaluate the effect of organisational commitment on employee security compliance intentions. Finally, we empirically test the theoretical model with a data set representing the survey responses of 312 employees from 78 organisations. Our results suggest that (a) threat perceptions about the severity of breaches and response perceptions of response efficacy, self-efficacy, and response costs are likely to affect policy attitudes; (b) organisational commitment and social influence have a significant impact on compliance intentions; and (c) resource availability is a significant factor in enhancing self-efficacy, which in turn, is a significant predictor of policy compliance intentions. We find that employees in our sample underestimate the probability of security breaches. European Journal of Information Systems (2009) 18, 106–125. doi:10.1057/ejis.2009.6; published online 21 April 2009
Light-cone averaging in cosmology: formalism and applications

We present a general gauge invariant formalism for defining cosmological averages that are relevant for observations based on light-like signals. Such averages involve either null hypersurfaces corresponding to a family of past light-cones or compact surfaces given by their intersection with timelike hypersurfaces. Generalized Buchert-Ehlers commutation rules for derivatives of these light-cone averages are given. After introducing some adapted “geodesic light-cone” coordinates, we give explicit expressions for averaging the redshift to luminosity-distance relation and the so-called “redshift drift” in a generic inhomogeneous Universe. ar X iv :1 10 4. 11 67 v3 [ as tr oph .C O ] 2 0 Ju n 20 11