nils-herrmann/clean_scirepeval huggingface dataset:
Learning to rank audience for behavioral targeting in display ads

Behavioral targeting (BT), which aims to sell advertisers those behaviorally related user segments to deliver their advertisements, is facing a bottleneck in serving the rapid growth of long tail advertisers. Due to the small business nature of the tail advertisers, they generally expect to accurately reach a small group of audience, which is hard to be satisfied by classical BT solutions with large size user segments. In this paper, we propose a novel probabilistic generative model named Rank Latent Dirichlet Allocation (RANKLDA) to rank audience according to their ads click probabilities for the long tail advertisers to deliver their ads. Based on the basic assumption that users who clicked the same group of ads will have a higher probability of sharing similar latent search topical interests, RANKLDA combines topic discovery from users' search behaviors and learning to rank users from their ads click behaviors together. In computation, the topic learning could be enhanced by the supervised information of the rank learning and simultaneously, the rank learning could be better optimized by considering the discovered topics as features. This co-optimization scheme enhances each other iteratively. Experiments over the real click-through log of display ads in a public ad network show that the proposed RANKLDA model can effectively rank the audience for the tail advertisers.
Tree-based Bayesian Mixture Model for Competing Risks

Many chronic diseases possess a shared biology. Therapies designed for patients at risk of multiple diseases need to account for the shared impact they may have on related diseases to ensure maximum overall well-being. Learning from data in this setting differs from classical survival analysis methods since the incidence of an event of interest may be obscured by other related competing events. We develop a semiparametric Bayesian regression model for survival analysis with competing risks, which can be used for jointly assessing a patient’s risk of multiple (competing) adverse outcomes. We construct a Hierarchical Bayesian Mixture (HBM) model to describe survival paths in which a patient’s covariates influence both the estimation of the type of adverse event and the subsequent survival trajectory through Multivariate Random Forests. In addition variable importance measures, which are essential for clinical interpretability are induced naturally by our model. We aim with this setting to provide accurate individual estimates but also interpretable conclusions for use as a clinical decision support tool. We compare our method with various state-of-the-art benchmarks on both synthetic and clinical data.
A small planar inverted-F antenna for wearable applications

Small printed antennas will replace the commonly used normal-mode helical antennas of mobile handsets and systems in the future. This paper presents a novel small planar inverted-F antenna (PIFA) which is a common PIFA in which a U-shaped slot is etched to form a dual band operation for wearable and ubiquitous computing equipment. Health issues are considered in selecting suitable antenna topology and the placement of the antenna. Various applications are presented while the paper mainly discusses about the GSM applications.
Going for gold: the health promoting general practice.

The World Health Organization's Ottawa Charter for Health Promotion has been influential in guiding the development of 'settings' based health promotion. Over the past decade, settings such as schools have flourished and there has been a considerable amount of academic literature produced, including theoretical papers, descriptive studies and evaluations. However, despite its central importance, the health-promoting general practice has received little attention. This paper discusses: the significance of this setting for health promotion; how a health promoting general practice can be created; effective health promotion approaches; the nursing contribution; and some challenges that need to be resolved. In order to become a health promoting general practice, the staff must undertake a commitment to fulfil the following conditions: create a healthy working environment; integrate health promotion into practice activities; and establish alliances with other relevant institutions and groups within the community. The health promoting general practice is the gold standard for health promotion. Settings that have developed have had the support of local, national and European networks. Similar assistance and advocacy will be needed in general practice. This paper recommends that a series of rigorously evaluated, high-quality pilot sites need to be established to identify and address potential difficulties, and to ensure that this innovative approach yields tangible health benefits for local communities. It also suggests that government support is critical to the future development of health promoting general practices. This will be needed both directly and in relation to the capacity and resourcing of public health in general.
MedWeb Task : Multi-label Classification of Tweets using an Ensemble of Neural Networks

This paper describes how we tackled the Medical Natural Language Processing for Web Document (MedWeb) task as participants of NTCIR13. We utilized multi-language learning to integrate the multi-language inputs of the task into a single neural network. We then built two neural networks–a hierarchical attention network (HAN) and a deep character convolutional neural network (CharCNN)–with multilanguage learning and combined both outputs to utilize the advantages of each neural network. This combination was carried out using ensembling, specifically the method of bagging. We found that the ensemble using the loss functions NLL and hinge produced the best results with 88.0% accuracy.
The anatomic basis of pure alexia.

The behavioral and anatomic correlates of pure alexia were analyzed in 16 patients. Right homonymous hemianopia failed to appear in three patients, who had right achromatopsia instead. Color anomia and unilateral optic ataxia were seen in six patients. Memory defects were found in two patients. Visual agnosia was noted in two. No patient had visual disorientation. The crucial anatomic correlate of alexia was a lesion of the paraventricular white matter of the left occipital lobe, capable of compromising both interhemispheric and intrahemispheric visual pathways. The lesion associated with color anomia was in the mesial occipitotemporal junction of the left hemisphere.
[The history of the concept of gender identity disorder].

The Metamorphoses Greek myth includes a story about a woman raised as a male falling in love with another woman, and being transformed into a man prior to a wedding ceremony and staying with her. It is therefore considered that people who desire to live as though they have the opposite gender have existed since ancient times. People who express a sense of discomfort with their anatomical sex and related roles have been reported in the medical literature since the middle of the 19th century. However, homosexual, fetishism, gender identity disorder, and associated conditions were mixed together and regarded as types of sexual perversion that were considered ethically objectionable until the 1950s. The first performance of sex-reassignment surgery in 1952 attracted considerable attention, and the sexologist Harry Benjamin reported a case of 'a woman kept in the body of a man', which was called transsexualism. John William Money studied the sexual consciousness about disorders of sex development and advocated the concept of gender in 1957. Thereafter the disparity between anatomical sex and gender identity was referred to as the psychopathological condition of gender identity disorder, and this was used for its diagnostic name when it was introduced into DSM-III in 1980. However, gender identity disorder encompasses a spectrum of conditions, and DSM-III -R categorized it into three types: transsexualism, nontranssexualism, and not otherwise specified. The first two types were subsequently combined and standardized into the official diagnostic name of 'gender identity disorder' in DSM-IV. In contrast, gender identity disorder was categorized into four groups (including transsexualism and dual-role transvestism) in ICD-10. A draft proposal of DSM-5 has been submitted, in which the diagnostic name of gender identity disorder has been changed to gender dysphoria. Also, it refers to 'assigned gender' rather than to 'sex', and includes disorders of sexual development. Moreover, the subclassifications regarding sexual orientation have been deleted. The proposed DSM-5 reflects an attempt to include only a medical designation of people who have suffered due to the gender disparity, thereby respecting the concept of transgender in accepting the diversity of the role of gender. This indicates that transgender issues are now at a turning point.
Spectral Transfer Learning Using Information Geometry for a User-Independent Brain-Computer Interface

Recent advances in signal processing and machine learning techniques have enabled the application of Brain-Computer Interface (BCI) technologies to fields such as medicine, industry, and recreation; however, BCIs still suffer from the requirement of frequent calibration sessions due to the intra- and inter-individual variability of brain-signals, which makes calibration suppression through transfer learning an area of increasing interest for the development of practical BCI systems. In this paper, we present an unsupervised transfer method (spectral transfer using information geometry, STIG), which ranks and combines unlabeled predictions from an ensemble of information geometry classifiers built on data from individual training subjects. The STIG method is validated in both off-line and real-time feedback analysis during a rapid serial visual presentation task (RSVP). For detection of single-trial, event-related potentials (ERPs), the proposed method can significantly outperform existing calibration-free techniques as well as outperform traditional within-subject calibration techniques when limited data is available. This method demonstrates that unsupervised transfer learning for single-trial detection in ERP-based BCIs can be achieved without the requirement of costly training data, representing a step-forward in the overall goal of achieving a practical user-independent BCI system.
Spectral Methods for Indian Buffet Process Inference

The Indian Buffet Process is a versatile statistical tool for modeling distributions over binary matrices. We provide an efficient spectral algorithm as an alternative to costly Variational Bayes and sampling-based algorithms. We derive a novel tensorial characterization of the moments of the Indian Buffet Process proper and for two of its applications. We give a computationally efficient iterative inference algorithm, concentration of measure bounds, and reconstruction guarantees. Our algorithm provides superior accuracy and cheaper computation than comparable Variational Bayesian approach on a number of reference problems.
Information Flow Control Models in Peer-to-Peer Publish/Subscribe Systems

A publish/subscribe (PS) model is an event-driven model of a distributed system. In this paper, we consider a peer-to-peer (P2P) type of PS model where each peer (process) can publish and subscribe events. Here, a peer publishes an event message and then the event message is notified to a target peer which is interested in the event. Publications and subscriptions are specified in terms of topics as discussed in topic-based PS systems. In this paper, we newly discuss a topic-based access control (TBAC) model to prevent illegal information flow among peers in PS systems. Here, an access right is a pair "t, op" of a topic t and an operation op which is publish or subscribe. A peer is allowed to publish an event message with topics and subscribe topics only if the topics are granted to the peer. An event message e is notified to a peer pi if the publication of e and subscription of pi include some common topic. If a peer pi publishes an event message e2 after receiving an event message e1, the event message e2 may bring the event of e1, which the peer pi is not allowed to publish. Here, information in the peer pi illegally flow to another peer. We define the legal flow relation among the peers. Then, we newly propose a subscription-based synchronization (SBS) protocol to prevent illegal information flow. Here, a notification is banned if the notification may cause illegal information flow. We evaluate the SBS protocol in terms of number of notifications banned.
MRI and CT appearances of cardiac tumours in adults.

Primary cardiac tumours are rare, and metastases to the heart are much more frequent. Myxoma is the commonest benign primary tumour and sarcomas account for the majority of malignant lesions. Clinical manifestations are diverse, non-specific, and governed by the location, size, and aggressiveness. Imaging plays a central role in their evaluation, and familiarity with characteristic features is essential to generate a meaningful differential diagnosis. Cardiac magnetic resonance imaging (MRI) has become the reference technique for evaluation of a suspected cardiac mass. Computed tomography (CT) provides complementary information and, with the advent of electrocardiographic gating, has become a powerful tool in its own right for cardiac morphological assessment. This paper reviews the MRI and CT features of primary and secondary cardiac malignancy. Important differential considerations and potential diagnostic pitfalls are also highlighted.
Multimodal theater: extending low fidelity paper prototyping to multimodal applications

Low-fidelity paper prototyping has proven to be a useful technique for designing graphical user interfaces . Wizard of Oz prototyping for other input modalities, such as speech, also has a long history . Yet to surface are guidelines for low-fidelity prototyping of multimodal applications, those that use multiple and sometimes simultaneous combination of different input types. This paper describes our recent research in low fidelity, multimodal, paper prototyping and suggest guidelines to be used by future designers of multimodal applications.
Selecting criteria to evaluate qualitative research ®

While the evaluation of quantitative research frequently depends on  judgements based on the “holy trinity” of objectivity, reliability and validity (Spencer, Ritchie, Lewis, & Dillon, 2003, p. 59), applying  these  traditional  criteria  to qualitative  research  is not always a “good  fit”  (Schofield, 2002).  Instead,  educational  researchers  who  engage  in  qualitative  research  have  suggested various  sets  of  alternative  criteria  including:  transferability,  generalisability,  ontological authenticity, reciprocity, dependability, confirmability, reflexivity, fittingness, vitality and, even, sacredness and goodness  (Creswell, 2002; Garman, 1996; Guba & Lincoln, 1989; Patton, 2002; Spencer et al., 2003; Stige, Malterud, & Midtgarden, 2009). While over one hundred sets of qualitative  research criteria have been  identified  (Stige et al., 2009),  some  researchers warn  against  the  absolute  application  of  any  criteria  to  qualitative research which is, by its nature, wide‐ranging and varied, and does not necessarily lend itself to the straightforward application of any evaluation criteria. Nevertheless, whether or not criteria are applied at all  in  the  research evaluation process, postgraduate  students  face a number of decisions associated with  the process of evaluating qualitative  research: 1) whether or not  to adopt a  set of appraisal criteria; 2) which  criteria  to  select,  if criteria are used; and 3) how  to apply  alternative  approaches  to  criteria‐focused  evaluation.  These  decisions  often  require  a paradigm  shift  (Khun,  1962)  in  the way  postgraduate  students  perceive  and  approach  their research. The messiness and complexity associated with such decisions can be confronting. This paper  examines  a  number  of  approaches  used  by  researchers  to  evaluate  qualitative investigations in educational research.
Three-Dimensional , Kinematic , Human Behavioral Pattern-Based Features for Multimodal Emotion Recognition

This paper presents a multimodal emotion recognition method that uses a feature-level combination of three-dimensional (3D) geometric features (coordinates, distance and angle of joints), kinematic features such as velocity and displacement of joints, and features extracted from daily behavioral patterns such as frequency of head nod, hand wave, and body gestures that represent specific emotions. Head, face, hand, body, and speech data were captured from 15 participants using an infrared sensor (Microsoft Kinect). The 3D geometric and kinematic features were developed using raw feature data from the visual channel. Human emotional behavior-based features were developed using inter-annotator agreement and commonly observed expressions, movements and postures associated to specific emotions. The features from each modality and the behavioral pattern-based features (head shake, arm retraction, body forward movement depicting anger) were combined to train the multimodal classifier for the emotion recognition system. The classifier was trained using 10-fold cross validation and support vector machine (SVM) to predict six basic emotions. The results showed improvement in emotion recognition accuracy (The precision increased by 3.28% and the recall rate by 3.17%) when the 3D geometric, kinematic, and human behavioral pattern-based features were combined for multimodal emotion recognition using supervised classification.
Association of Therapy for Autoimmune Disease With Myelodysplastic Syndromes and Acute Myeloid Leukemia.

Therapy-related myeloid neoplasms are a potentially life-threatening consequence of treatment for autoimmune disease (AID) and an emerging clinical phenomenon.



To query the association of cytotoxic, anti-inflammatory, and immunomodulating agents to treat patients with AID with the risk for developing myeloid neoplasm.



This retrospective case-control study and medical record review included 40 011 patients with an International Classification of Diseases, Ninth Revision, coded diagnosis of primary AID who were seen at 2 centers from January 1, 2004, to December 31, 2014; of these, 311 patients had a concomitant coded diagnosis of myelodysplastic syndrome (MDS) or acute myeloid leukemia (AML). Eighty-six cases met strict inclusion criteria. A case-control match was performed at a 2:1 ratio.



Odds ratio (OR) assessment for AID-directed therapies.



Among the 86 patients who met inclusion criteria (49 men [57%]; 37 women [43%]; mean [SD] age, 72.3 [15.6] years), 55 (64.0%) had MDS, 21 (24.4%) had de novo AML, and 10 (11.6%) had AML and a history of MDS. Rheumatoid arthritis (23 [26.7%]), psoriasis (18 [20.9%]), and systemic lupus erythematosus (12 [14.0%]) were the most common autoimmune profiles. Median time from onset of AID to diagnosis of myeloid neoplasm was 8 (interquartile range, 4-15) years. A total of 57 of 86 cases (66.3%) received a cytotoxic or an immunomodulating agent. In the comparison group of 172 controls (98 men [57.0%]; 74 women [43.0%]; mean [SD] age, 72.7 [13.8] years), 105 (61.0%) received either agent (P = .50). Azathioprine sodium use was observed more frequently in cases (odds ratio [OR], 7.05; 95% CI, 2.35- 21.13; P < .001). Notable but insignificant case cohort use among cytotoxic agents was found for exposure to cyclophosphamide (OR, 3.58; 95% CI, 0.91-14.11) followed by mitoxantrone hydrochloride (OR, 2.73; 95% CI, 0.23-33.0). Methotrexate sodium (OR, 0.60; 95% CI, 0.29-1.22), mercaptopurine (OR, 0.62; 95% CI, 0.15-2.53), and mycophenolate mofetil hydrochloride (OR, 0.66; 95% CI, 0.21-2.03) had favorable ORs that were not statistically significant. No significant association between a specific length of time of exposure to an agent and the drug's category was observed.



In a large population with primary AID, azathioprine exposure was associated with a 7-fold risk for myeloid neoplasm. The control and case cohorts had similar systemic exposures by agent category. No association was found for anti-tumor necrosis factor agents. Finally, no timeline was found for the association of drug exposure with the incidence in development of myeloid neoplasm.
Nurse moral distress: A survey identifying predictors and potential interventions.

Ethical dilemmas and conflicts are inherent in today's health care organizations and may lead to moral distress, which is often associated with physical and psychological symptoms. Although the existence of moral distress has been observed by scholars for decades, most of the research has been descriptive and has examined what types of health care conflicts lead to distress.



This study tested a comprehensive model, underpinned by Social Cognitive Theory, that examined work environment and intrapersonal variables that may influence moral distress.



We surveyed nursing staff employed in a U.S. acute care hospital (response rate=45%; n=290).



More than half of the respondents reported they experience ethical dilemmas and conflicts from several times a month to daily, and nearly half reported they experience moral distress at least several times a month. Structural equation modeling analysis simultaneously examined the effects of five independent variables on moral distress and moral voice: (a) frequency of ethical dilemmas and conflicts; (b) moral efficacy; (c) ethics communication; (d) ethical environment; and (e) organizational ethics support. Results revealed significant independent effects of the frequency of ethics issues and organizational ethics support on moral distress. Bootstrapping analysis indicated that voice fully mediated the relationship between moral efficacy and moral distress, and partially mediated the relationship between organizational ethics support and distress. Supplemental analysis revealed that organizational ethics support moderated the moral efficacy-voice-moral distress relationship such that when organizational support was low, moral efficacy was negatively related to moral distress via voice.



Although it may be impossible to eliminate all ethical dilemmas and conflicts, leaders and organizations may wish to help improve nurses' moral efficacy, which appears to give rise to voice, and reduced moral distress. Increasing organizational ethics support may be a key approach.
Telemonitoring with respect to Mood Disorders and Information and Communication Technologies: Overview and Presentation of the PSYCHE Project

This paper reviews what we know about prediction in relation to mood disorders from the perspective of clinical, biological, and physiological markers. It then also presents how information and communication technologies have developed in the field of mood disorders, from the first steps, for example, the transition from paper and pencil to more sophisticated methods, to the development of ecological momentary assessment methods and, more recently, wearable systems. These recent developments have paved the way for the use of integrative approaches capable of assessing multiple variables. The PSYCHE project stands for Personalised monitoring SYstems for Care in mental HEalth.
An implementation of SLAM with extended Kalman filter

This paper discusses an implementation of Extended Kalman filter (EKF) in performing Simultaneous Localization and Mapping (SLAM). The implementation is divided into software and hardware phases. The software implementation applies EKF using Python on a library dataset to produce a map of the supposed environment. The result was verified against the original map and found to be relatively accurate with minor inaccuracies. In the hardware implementation stage, real life data was gathered from an indoor environment via a laser range finder and a pair of wheel encoders placed on a mobile robot. The resulting map shows at least five marked inaccuracies but the overall form is passable.