LLukas22/scidocs huggingface dataset:
FRank: a ranking method with fidelity loss

Ranking problem is becoming important in many fields, especially in information retrieval (IR). Many machine learning techniques have been proposed for ranking problem, such as RankSVM, RankBoost, and RankNet. Among them, RankNet, which is based on a probabilistic ranking framework, is leading to promising results and has been applied to a commercial Web search engine. In this paper we conduct further study on the probabilistic ranking framework and provide a novel loss function named fidelity loss for measuring loss of ranking. The fidelity loss notonly inherits effective properties of the probabilistic ranking framework in RankNet, but possesses new properties that are helpful for ranking. This includes the fidelity loss obtaining zero for each document pair, and having a finite upper bound that is necessary for conducting query-level normalization. We also propose an algorithm named FRank based on a generalized additive model for the sake of minimizing the fedelity loss and learning an effective ranking function. We evaluated the proposed algorithm for two datasets: TREC dataset and real Web search dataset. The experimental results show that the proposed FRank algorithm outperforms other learning-based ranking methods on both conventional IR problem and Web search.
Health status assessment tool for the family member caregiver of patients with bipolar disorder: development and psychometric testing.

INTRODUCTION
The caregivers' health assessment requires the application of a valid instrument that provided based on their experiences about the health concept. The purpose of this study was to develop and test the psychometric properties of the health assessment tool for family member caregivers' of patients with bipolar disorder.


METHODS
This study utilized mixed research. The specific validation processes used were: content and face validity, construct validity using factor analysis, reliability and internal consistency using test-retest reliability and Cronbach's alpha correlation coefficient.


RESULTS
The exploratory factor analysis revealed ten factors: safe life with peace, maintaining physical health, painful emotions, psychological tolerance, maintaining physical-psychological potency, families and relatives support, health care system support, moral-financial support, maintaining social relationships, and worry over the label. The internal consistency (Cronbach's alpha) was 95. Test-retest reliability of the questionnaire with interval time of two weeks was 0.93 (p < 0.001).


CONCLUSION
Family caregivers' health assessment questionnaire with 75 items helped to determine family caregivers' health in different settings such as clinical settings, homes and research environments by health care providers.
Spectral embedding of graphs

In this paper we explore how to embed symbolic relational graphs with unweighted edges in a pattern-space. We adopt a graph-spectral approach. We use the leading eigenvectors of the graph adjacency matrix to de0ne eigenmodes of the adjacency matrix. For each eigenmode, we compute vectors of spectral properties. These include the eigenmode perimeter, eigenmode volume, Cheeger number, inter-mode adjacency matrices and intermode edge-distance. We embed these vectors in a pattern-space using two contrasting approaches. The 0rst of these involves performing principal or independent components analysis on the covariance matrix for the spectral pattern vectors. The second approach involves performing multidimensional scaling on the L2 norm for pairs of pattern vectors. We illustrate the utility of the embedding methods on neighbourhood graphs representing the arrangement of corner features in 2D images of 3D polyhedral objects. Two problems are investigated. The 0rst of these is the clustering of graphs representing distinct objects viewed from di4erent directions. The second is the identi0cation of characteristic views of single objects. These two studies reveal that both embedding methods result in well-structured view spaces for graph-data extracted from 2D views of 3D objects. ? 2003 Pattern Recognition Society. Published by Elsevier Science Ltd. All rights reserved.
THE IMPLICATION OF THE LEARNING THEORIES ON IMPLEMENTING E-LEARNING COURSES

The aim of this paper is to describe the implication of the three commonly known learning theories on online courses. These theories are: the behaviorism, cognitivism, and constructivism. Moreover, the effect of these learning theories on implementing e-learning courses is reported. The description of the implication of these learning theories can help to develop the process of learning for the learner. Online learning materials should include activities for the different learning styles, so that learners can select appropriate activities based on their preferred style. Thus, a shift to pedagogy-based initiatives can be observed within the field of elearning. In this paper, these three theories are described in short, and implications for realizing online courses are derived. General Terms: Theory
HIGH-IMPEDANCE SURFACES BASED ON SELF-RESONANT GRIDS. ANALYTICAL MODELLING AND NUMERICAL SIMULATIONS

A new variant of artificial high-impedance surfaces is suggested and studied. This is a thin composite layer consisting of a dielectric layer with a planar self-resonant grid from metal strips on its surface. Every grid element is connected to the ground plane with a metal pin. We use an analytical model which has been recently developed for a similar structure. The advantages of the new structure (decreasing the resonant frequency for fixed period and thickness, further angular stabilization of surface impedance for the TE-incidence of waves) are studied and explained. The analytical model is compared with numerical simulations. It predicts quite well the resonant frequencies of the artificial surface for different angles of incidence however is not enough accurate for calculating the values of the surface impedance.
A biodegradable hydrogel system containing curcumin encapsulated in micelles for cutaneous wound healing.

A biodegradable in situ gel-forming controlled drug delivery system composed of curcumin loaded micelles and thermosensitive hydrogel was prepared and applied for cutaneous wound repair. Curcumin is believed to be a potent antioxidant and anti-inflammatory agent. Due to its high hydrophobicity, curcumin was encapsulated in polymeric micelles (Cur-M) with high drug loading and encapsulation efficiency. Cur-M loaded thermosensitive hydrogel (Cur-M-H) was prepared and applied as wound dressing to enhance the cutaneous wound healing. Cur-M-H was a free-flowing sol at ambient temperature and instantly converted into a non-flowing gel at body temperature. In vitro studies suggested that Cur-M-H exhibited well tissue adhesiveness and could release curcumin in an extended period. Furthermore, linear incision and full-thickness excision wound models were employed to evaluate the in vivo wound healing activity of Cur-M-H. In incision model, Cur-M-H-treated group showed higher tensile strength and thicker epidermis. In excision model, Cur-M-H group exhibited enhancement of wound closure. Besides, in both models, Cur-M-H-treated groups showed higher collagen content, better granulation, higher wound maturity, dramatic decrease in superoxide dismutase, and slight increase in catalase. Histopathologic examination also implied that Cur-M-H could enhance cutaneous wound repair. In conclusion, biodegradable Cur-M-H composite might have great application for wound healing.
Quantifier Elimination for a Class of Intuitionistic Theories

From classical, Fraisse-homogeneous, (≤ ω)-categorical theories over finite relational languages (which we refer to as JRS theories), we construct intuitionistic theories that are complete, prove negations of classical tautologies, and admit quantifier elimination. The technique we use considers Kripke models as functors from a small category to the category of L-structures with morphisms, rather than the usual interpretation wherein the frame of a Kripke model is a partial order. While one can always “unravel” a functor Kripke model to obtain a partial order Kripke model with the same intuitionistic theory, our technique is perhaps an easier way to consider a Kripke model that includes a single classical node structure and all of the endomorphisms of that classical JRS structure. We also determine the intuitionistic universal fragments of these theories, in accordance with the hierarchy of intuitionistic formulas put forth in [9] and expounded on by Fleischmann in [11]. This portion of the thesis (Chapter 1) is the result of joint work with Ben Ellison, Jonathan Fleischmann, and Wim Ruitenburg, as published (up to minor structural changes) in [10]. Given a classical JRS theory, we determine axiomatizations of the corresponding intuitionistic theory in Chapter 2. We first do so by axiomatizing properties apparent from the behavior of the model, and discuss improvements to that axiom system. We then present another axiomatization, this time by axiomatizing the properties of quantifier elimination. We discuss improvements to this system, and show how this system and various subsystems thereof are equivalent to our first axiomatization and corresponding subsystems thereof.
Enterprise cloud service architectures

As a new computing paradigm, cloud computing has received a lot of attention from enterprises and has being integrated or applied to enterprise architectures. This paper surveys the state of the art of enterprise cloud service architectures. Specifically, this paper discusses enterprise cloud service architectural requirements, design approaches, architectural styles, emerging cloud service platforms, applications and related challenges in an enterprise context. This paper also identifies research trends and opportunities for researchers and practitioners in this fast moving field.
Morphological Abnormalities of Thalamic Subnuclei in Migraine: A Multicenter MRI Study at 3 Tesla.

UNLABELLED
The thalamus contains third-order relay neurons of the trigeminal system, and animal models as well as preliminary imaging studies in small cohorts of migraine patients have suggested a role of the thalamus in headache pathophysiology. However, larger studies using advanced imaging techniques in substantial patient populations are lacking. In the present study, we investigated changes of thalamic volume and shape in a large multicenter cohort of patients with migraine. High-resolution T1-weighted MRI data acquired at 3 tesla in 131 patients with migraine (38 with aura; 30.8 ± 9 years old; 109 women; monthly attack frequency: 3.2 ± 2.5; disease duration: 14 ± 8.4 years) and 115 matched healthy subjects (29 ± 7 years old; 81 women) from four international tertiary headache centers were analyzed. The thalamus and thalamic subnuclei, striatum, and globus pallidus were segmented using a fully automated multiatlas approach. Deformation-based shape analysis was performed to localize surface abnormalities. Differences between patients with migraine and healthy subjects were assessed using an ANCOVA model. After correction for multiple comparisons, performed using the false discovery rate approach (p < 0.05 corrected), significant volume reductions of the following thalamic nuclei were observed in migraineurs: central nuclear complex (F(1,233) = 6.79), anterior nucleus (F(1,237) = 7.38), and lateral dorsal nucleus (F(1,238) = 6.79). Moreover, reduced striatal volume (F(1,238) = 6.9) was observed in patients. This large-scale study indicates structural thalamic abnormalities in patients with migraine. The thalamic nuclei with abnormal volumes are densely connected to the limbic system. The data hence lend support to the view that higher-order integration systems are altered in migraine.


SIGNIFICANCE STATEMENT
This multicenter imaging study shows morphological thalamic abnormalities in a large cohort of patients with episodic migraine compared with healthy subjects using state-of-the-art MRI and advanced, fully automated multiatlas segmentation techniques. The results stress that migraine is a disorder of the CNS in which not only is brain function abnormal, but also brain structure is undergoing significant remodeling.
Conflicting Implementation of Agricultural and Water Policies in Irrigated Areas in the EU

Irrigated agriculture is directly influenced by various EU policies, especially the CAP and more recently the Water Framework Directive (WFD). The demand for water by agriculture is largely determined by CAP policy. On the other hand, the objective of the WFD is to regulate the supply (cost, quality, quantity) of water to agriculture. This work examines the relationships between these two policy instruments and applies a scenario analysis to a case study in central Spain using a multi-criteria model of farmer behaviour. The results show that the two instruments must be co-ordinated in order to meet socio-economic goals (farmers’ income and labour demand) and environmental protection (water-use efficiency).
Multilingual named entity extraction and translation from text and speech

Named entity (NE), the noun or noun phrases referring to persons, locations and organizations, are among the most informationbearing linguistic structures. Extracting and translating named entities benefits many natural language processing problems such as cross-lingual information retrieval, cross-lingual question answering and machine translation. In this thesis work we propose an efficient and effective framework to extract and translate NEs from text and speech. We adopt the hidden Markov model (HMM) as our baseline NE extraction system, and investigate its performance in multiple language pairs with varying amount of training data. We expand the baseline text NE tagger with a context-based NE extraction model, which aims to detect and correct NE recognition errors from automatic speech recognition hypotheses. We also adapt the broadcast news trained NE tagger for meeting transcripts. We develop several language-independent features to capture phonetic and semantic similarity measures between source and target NE pairs. We incorporate these features to solve various NE translation problems presented in different language pairs (Chinese to English, Arabic to English and Hindi to English), with varying resources (parallel and non-parallel corpora as well as the world wide web) and different input data streams (text and speech). We also propose a cluster-specific name transliteration framework. By grouping names from similar origins into one cluster and train cluster-specific transliteration and language models, we manage to dramatically reduce the name transliteration error rates.
Factors that Mediate Flight Plan Monitoring and Errors in Plan Revision: Planning Under Automated and High Workload Conditions

An experiment was conducted to explore the effects of automation and task loading on aviation plan monitoring and errors in plan revision. Pilots were asked to select one of two flight paths that traversed through hazardous airspace and to then monitor the safety of the path by seeking and reporting changes in dynamic traffic aircraft and weather systems. Following change detection, pilots were given the opportunity to revise their flight plan as a result of the changes. Attention guidance automation, which was reliable for plan selection, but failed to highlight a critical change that threatened safety after plan selection, was present on half of trials. Automation improved planning accuracy and confidence in high workload conditions. However, in nearly one third of trials, pilots failed to revise the flight plans as a result of a change, and were more likely to do so with imperfect automation in high workload.
Effects of yoga on depression and anxiety of women.

UNLABELLED
Yoga has often been perceived as a method of stress management tool that can assist in alleviating depression and anxiety disorders. This study sought to evaluate the influence of yoga in relieving symptoms of depression and anxiety in women who were referred to a yoga clinic.


METHODS
The study involved a convenience sample of women who were referred to a yoga clinic from July 2006 to July 2007. All new cases were evaluated on admission using a personal information questionnaire well as Beck and Spielberger tests. Participants were randomly assigned into an experimental and a control group. The experimental group (n=34) participated in twice weekly yoga classes of 90 min duration for two months. The control group (n=31) was assigned to a waiting list and did not receive yoga. Both groups were evaluated again after the two-month study period.


RESULTS
The average prevalence of depression in the experimental group pre and post Yoga intervention was 12.82+/-7.9 and 10.79+/-6.04 respectively, a statistically insignificant decrease (p=0.13). However, when the experimental group was compared to the control group, women who participated in yoga classes showed a significant decrease in state anxiety (p=0.03) and trait anxiety (p<0.001).


CONCLUSIONS
Participation in a two-month yoga class can lead to significant reduction in perceived levels of anxiety in women who suffer from anxiety disorders. This study suggests that yoga can be considered as a complementary therapy or an alternative method for medical therapy in the treatment of anxiety disorders.
Food waste reduction practices in German food retail

Purpose
The purpose of this paper is to investigate food retailers food waste reduction practices in Germany. The focus is on selling and redistributing agricultural produce with visual impairments and other surplus food items. In addition, drivers and barriers regarding the implementation of both waste reduction practices are explored.


Design/methodology/approach
In total, 12 in-depth interviews with managerial actors in the food retail sector and a food bank spokesperson were recorded, transcribed and analyzed through a qualitative content analysis.


Findings
In contrast to organic retailers, conventional retailers were reluctant to include agricultural produce with visual impairments in their product assortments, due to fears of negative consumer reactions. Another obstacle was EU marketing standards for specific produce. All retailers interviewed engaged in redistribution of surplus food. Logistics and the regulatory framework were the main barriers to food redistribution.


Originality/value
The present study adds to the existing body of literature on food waste reduction practices as it explores selling produce with visual impairments and elaborates on the legal background of food redistribution in German retail. The results are the foundation for providing recommendations to policy makers and charitable food organizations.
A new rule-based algorithm for identifying metabolic markers in prostate cancer using tandem mass spectrometry

MOTIVATION
Prostate cancer is the most prevalent tumor in males and its incidence is expected to increase as the population ages. Prostate cancer is treatable by excision if detected at an early enough stage. The challenges of early diagnosis require the discovery of novel biomarkers and tools for prostate cancer management.


RESULTS
We developed a novel feature selection algorithm termed as associative voting (AV) for identifying biomarker candidates in prostate cancer data measured via targeted metabolite profiling MS/MS analysis. We benchmarked our algorithm against two standard entropy-based and correlation-based feature selection methods [Information Gain (IG) and ReliefF (RF)] and observed that, on a variety of classification tasks in prostate cancer diagnosis, our algorithm identified subsets of biomarker candidates that are both smaller and show higher discriminatory power than the subsets identified by IG and RF. A literature study confirms that the highest ranked biomarker candidates identified by AV have independently been identified as important factors in prostate cancer development.


AVAILABILITY
The algorithm can be downloaded from the following http://biomed.umit.at/page.cfm?pageid=516.
Objective responses in relapsed T-cell lymphomas with single-agent brentuximab vedotin.

This phase 2, open-label, multicenter study evaluated the efficacy and safety of brentuximab vedotin, a CD30-directed antibody-drug conjugate, in relapsed/refractory CD30(+) non-Hodgkin lymphomas. The primary end point was objective response rate (ORR). Key secondary end points included safety, correlation of CD30 expression with response, response duration, and progression-free survival (PFS). Brentuximab vedotin 1.8 mg/kg was administered every 3 weeks until progression or unacceptable toxicity. This planned subset analysis included patients with peripheral T-cell lymphomas (PTCLs; n = 35), specifically angioimmunoblastic T-cell lymphoma (AITL; n = 13) and PTCL not otherwise specified (n = 22). Median age was 64 years; 63% were refractory to most recent therapy. Of 34 evaluable patients, ORR was 41% (8 complete remissions [CRs], 6 partial remissions [PRs]), and ORR was 54% in AITL (5 CRs, 2 PRs) with median PFS of 6.7 months thus far. No correlation between CD30 expression per central review and response was observed. Safety data were consistent with the known profile of brentuximab vedotin, and included at least grade 3 events of neutropenia (14%), peripheral sensory neuropathy, and hyperkalemia (9% each). In summary, brentuximab vedotin showed antitumor activity in patients with relapsed PTCL particularly AITL. This trial was registered at www.clinicaltrials.gov as #NCT01421667.
Moby and Moby 2: Creatures of the Deep (Web)

Facile and meaningful integration of data from disparate resources is the 'holy grail' of bioinformatics. Some resources have begun to address this problem by providing their data using Semantic Web standards, specifically the Resource Description Framework (RDF) and the Web Ontology Language (OWL). Unfortunately, adoption of Semantic Web standards has been slow overall, and even in cases where the standards are being utilized, interconnectivity between resources is rare. In response, we have seen the emergence of centralized 'semantic warehouses' that collect public data from third parties, integrate it, translate it into OWL/RDF and provide it to the community as a unified and queryable resource. One limitation of the warehouse approach is that queries are confined to the resources that have been selected for inclusion. A related problem, perhaps of greater concern, is that the majority of bioinformatics data exists in the 'Deep Web'-that is, the data does not exist until an application or analytical tool is invoked, and therefore does not have a predictable Web address. The inability to utilize Uniform Resource Identifiers (URIs) to address this data is a barrier to its accessibility via URI-centric Semantic Web technologies. Here we examine 'The State of the Union' for the adoption of Semantic Web standards in the health care and life sciences domain by key bioinformatics resources, explore the nature and connectivity of several community-driven semantic warehousing projects, and report on our own progress with the CardioSHARE/Moby-2 project, which aims to make the resources of the Deep Web transparently accessible through SPARQL queries.