LLukas22/scidocs huggingface dataset:
An X-linked channelopathy with cardiomegaly due to a CLIC2 mutation enhancing ryanodine receptor channel activity.

Chloride intracellular channel 2 (CLIC2) protein is a member of the glutathione transferase class of proteins. Its' only known function is the regulation of ryanodine receptor (RyR) intracellular Ca(2+) release channels. These RyR proteins play a major role in the regulation of Ca(2+) signaling in many cells. Utilizing exome capture and deep sequencing of genes on the X-chromosome, we have identified a mutation in CLIC2 (c.303C>G, p.H101Q) which is associated with X-linked intellectual disability (ID), atrial fibrillation, cardiomegaly, congestive heart failure (CHF), some somatic features and seizures. Functional studies of the H101Q variant indicated that it stimulated rather than inhibited the action of RyR channels, with channels remaining open for longer times and potentially amplifying Ca(2+) signals dependent on RyR channel activity. The overly active RyRs in cardiac and skeletal muscle cells and neuronal cells would result in abnormal cardiac function and trigger post-synaptic pathways and neurotransmitter release. The presence of both cardiomegaly and CHF in the two affected males and atrial fibrillation in one are consistent with abnormal RyR2 channel function. Since the dysfunction of RyR2 channels in the brain via 'leaky mutations' can result in mild developmental delay and seizures, our data also suggest a vital role for the CLIC2 protein in maintaining normal cognitive function via its interaction with RyRs in the brain. Therefore, our patients appear to suffer from a new channelopathy comprised of ID, seizures and cardiac problems because of enhanced Ca(2+) release through RyRs in neuronal cells and cardiac muscle cells.
Schema and ontology matching with COMA++

We demonstrate the schema and ontology matching tool COMA++. It extends our previous prototype COMA utilizing a composite approach to combine different match algorithms [3]. COMA++ implements significant improvements and offers a comprehensive infrastructure to solve large real-world match problems. It comes with a graphical interface enabling a variety of user interactions. Using a generic data representation, COMA++ uniformly supports schemas and ontologies, e.g. the powerful standard languages W3C XML Schema and OWL. COMA++ includes new approaches for ontology matching, in particular the utilization of shared taxonomies. Furthermore, different match strategies can be applied including various forms of reusing previously determined match results and a so-called fragment-based match approach which decomposes a large match problem into smaller problems. Finally, COMA++ cannot only be used to solve match problems but also to comparatively evaluate the effectiveness of different match algorithms and strategies.
Leveraging on social media to support the global building resilient cities campaign

This paper presents a summary of the main points put forward during the presentation delivered at the 2nd International Workshop on Social Web for Disaster Management which was held in conjunction with WWW 2013 on May 14th 2013 in Rio de Janeiro, Brazil.
A presentation of Quantum Logic based on an "and then" connective

When a physicist performs a quantic measurement, new information about the system at hand is gathered. This article studies the logical properties of how this new information is combined with previous information. It presents Quantum Logic as a propositional logic under two connectives: negation and the and then operation that combines old and new information. The and then connective is neither commutative nor associative. Many properties of this logic are exhibited, and some small elegant subset is shown to imply all the properties considered. No independence or completeness result is claimed. Classical physical systems are exactly characterized by the commutativity, the associativity, or the monotonicity of the and then connective. Entailment is defined in this logic and can be proved to be a partial order. In orthomodular lattices, the operation proposed by Finch in [3] satisfies all the properties studied in this article. All properties satisfied by Finch's; operation in modular lattices are valid in Quantum Logic. It is not known whether all properties of Quantum Logic are satisfied by Finch's; operation in modular lattices. Non-commutative, non-associative algebraic structures generalizing Boolean algebras are defined, ideals are characterized and a homomorphism theorem is proved.
The Socialbot Network : When Bots Socialize for Fame & Money

A new breed of computer programs called socialbots are now online, and they can be used to breach users’ privacy, spread misinformation to bias the public opinion, and compromise the graph of a targeted social network [1, 2]. A socialbot controls a fictitious user profile and has the ability to execute basic online activities (e.g., posting a message, sending a connection request). What makes a socialbot different from other self-declared bots (e.g., bots posting weather forecasts in Twitter) is that it is designed to infiltrate online communities by passing itself off as a human being. Socialbots can be used to manipulate the graph of a targeted social network in order to establish a centralized or influential social position in it. This position can be then exploited to mount DDoS attacks, promote products, or to spread propaganda in a viral way. For example, Ratkiewicz et al. [2] described the use of Twitter bots to spread misinformation in the run-up to the US political elections. As the socialbots infiltrate a targeted social network, they also harvest valuable users’ data which is useful for online profiling and large-scale spam campaigns. In fact, a new report showed that spammers are turning to online social networking platforms for distributing their messages [7], which explains the dramatic drop in the world-wide email spam during the recent months [6]. This gave rise to black-market businesses that offer multi-featured socialbots for as high as $29 per bot [3]. Many techniques have been proposed that try to identify socialbots based on their likely unordinary behavior (see [4] for an example on Twitter). In this research, we take a proactive step and investigate the feasibility of operating an organized army of socialbots which we call a Socialbot Network (SbN). A SbN is a group of socialbots that collaborate in infiltrating social networks under the orchestration of one or many “master” bots. We study the security and privacy implications of operating such a SbN on a large scale. In particular, we answer questions about the types of collaboration these socialbots can utilize, the required infrastructure, the network-wide observations that can be exploited to improve the potential infiltration, and the economics of operating a SbN on a large scale. Finally, we present a set of challenges that future social network security systems have to overcome in order to mitigate the potential threat of a SbN.
Quality improvement in heart failure: a randomized educational intervention to change provider behavior.

UNLABELLED
Whether provider education changes practice for HF has not been reported. (NHeFT)™ uses didactic and experiential training of primary care providers (PCP) to optimize treatment of HF. We randomized PCP's in the Cleveland VA clinics to training (T) vs control (C).


ENDPOINTS
Primary - the number of patients with EF < 40% treated with ACEI/ARB and Beta Blocker, +/- diuretic post T vs pre T; Secondary - the number of patients with increase in ACEI/ARB or a decrease in diuretic post T vs. pre T. Of 641 patients, 216 (85 C,131 T) had EF < 40%; 188 (85%) did not meet the primary endpoint at baseline. After T, a similar proportion (64.2% C, 74.4%,T) met the endpoint at end of study (P = 0.14). The odds of a patient meeting the primary endpoint by care of a T provider, was not significantly higher than C (OR 1.496, 95% CI (0.751, 2.982)). Patients seen by T were more likely to have the diuretic dose decreased vs patients under C, without increases in ACEI or ARB (P < 0.03). Thus, a didactic program of HF plus a preceptorship changed practice modestly. Studies should address provider readiness of change and self efficacy to adhere to evidenced-based care.
Automated unsupervised multi-parametric classification of adipose tissue depots in skeletal muscle.

PURPOSE
To introduce and validate an automated unsupervised multi-parametric method for segmentation of the subcutaneous fat and muscle regions to determine subcutaneous adipose tissue (SAT) and intermuscular adipose tissue (IMAT) areas based on data from a quantitative chemical shift-based water-fat separation approach.


MATERIALS AND METHODS
Unsupervised standard k-means clustering was used to define sets of similar features (k = 2) within the whole multi-modal image after the water-fat separation. The automated image processing chain was composed of three primary stages: tissue, muscle, and bone region segmentation. The algorithm was applied on calf and thigh datasets to compute SAT and IMAT areas and was compared with a manual segmentation.


RESULTS
The IMAT area using the automatic segmentation had excellent agreement with the IMAT area using the manual segmentation for all the cases in the thigh (R(2): 0.96) and for cases with up to moderate IMAT area in the calf (R(2): 0.92). The group with the highest grade of muscle fat infiltration in the calf had the highest error in the inner SAT contour calculation.


CONCLUSION
The proposed multi-parametric segmentation approach combined with quantitative water-fat imaging provides an accurate and reliable method for an automated calculation of the SAT and IMAT areas reducing considerably the total postprocessing time.
Manual vs. automatic capture management in implantable cardioverter defibrillators and cardiac resynchronization therapy defibrillators

AIMS
The Secura ICD and Consulta CRT-D are the first defibrillators to have automatic right atrial (RA), right ventricular (RV), and left ventricular (LV) capture management (CM). Complete CM was evaluated in an implantable cardioverter defibrillator (ICD) population.


METHODS AND RESULTS
Two prospective clinical studies were conducted in 28 centres in Europe and Israel. Automatic CM data were compared with manual threshold measurements, the CM applicability was determined, and adjustments to pacing outputs were analysed. In total, 160 patients [age 64.6 +/- 10.4 years, 77% male, 80 ICD and 80 cardiac resynchronization therapy defibrillator (CRT-D)] were included. The differences between automatic and manual measurements were </=0.25 V in 97% (RA CM) and 96% (RV CM) and were all within the safety margin. Fully automatic CM measurements were available within 1 week prior to the 3-month visit in 90% (RA), 99% (RV), and 97% (LV) of the patients. Results indicated increased output (threshold >2.5 V) due to raised RA threshold in seven (4.4%), high RV threshold in nine (5.6%), and high LV threshold in three patients (3.8%). All high threshold detections and all automatic modulations of pacing output were adjudicated appropriate.


CONCLUSION
Complete CM adjusts pacing output appropriately, permitting a reduction in office visits while it may maximize device longevity. The study was registered at ClinicalTrials.gov identifiers: NCT00526227 and NCT00526162.
A cohesive approach to thin-shell fracture and fragmentation

We develop a finite-element method for the simulation of dyna mic fracture and fragmentation of thin-shells. The shell is spatially discretized w ith subdivision shell elements and the fracture along the element edges is modeled with a cohesive l aw. In order to follow the propagation and branching of cracks, subdivision shell element s are pre-fracturedab initio and the crack opening is constrained prior to crack nucleation. Thi s approach allows for shell fracture in an in-plane tearing mode, a shearing mode, or a bending of h inge mode. The good performance of the method is demonstrated through the simulation o f petalling failure experiments in aluminum plates.
An Annotated Corpus for Machine Reading of Instructions in Wet Lab Protocols

1. Andrew Borthwick and Ralph Grishman. 1999. A maximum entropy approach to named entity recognition. Ph. D. Thesis, Dept. of Computer Science, New York University. 2. Alan Graves, Abdel-rahman Mohamed, and Geoffrey Hinton. 2013. Speech recognition with deep recurrent neural networks. In Proceedings of the 2013 IEEE International Conference on Acoustics, Speech and Signal Processing, pages 6645–6649. 3. Xuezhe Ma and Eduard Hovy. 2016. End-to-end se-quence labeling via bi-directional lstm-cnns-crf. In Proceedings of the 54th Annual Meeting of the Association for Computational Linguistics (ACL). The Ohio State University
Magnetic resonance electrical impedance tomography (MREIT): conductivity and current density imaging

This paper reviews the latest impedance imaging technique called Magnetic Resonance Electrical Impedance Tomography (MREIT) providing information on electrical conductivity and current density distributions inside an electrically conducting domain such as the human body. The motivation for this research is explained by discussing conductivity changes related with physiological and pathological events, electromagnetic source imaging and electromagnetic stimulations. We briefly summarize the related technique of Electrical Impedance Tomography (EIT) that deals with cross-sectional image reconstructions of conductivity distributions from boundary measurements of current-voltage data. Noting that EIT suffers from the ill-posed nature of the corresponding inverse problem, we introduce MREIT as a new conductivity imaging modality providing images with better spatial resolution and accuracy. MREIT utilizes internal information on the induced magnetic field in addition to the boundary current-voltage measurements to produce three-dimensional images of conductivity and current density distributions. Mathematical theory, algorithms, and experimental methods of current MREIT research are described. With numerous potential applications in mind, future research directions in MREIT are proposed.
Mental health nursing and stress: maintaining balance.

The recruitment and retention of mental health nurses within acute inpatient mental health facilities continues to be an ongoing issue. Literature and current research highlight an environment fraught with pressure and stress, identifying several key factors contributing to job dissatisfaction. These factors include greater patient acuity, unpredictable and challenging workspaces, violence, increased paperwork, and reduced managerial support. This qualitative, critical, feminist exploration investigated the lived experiences of 13 female mental health nurses working in inpatient services. They were asked about their practice and perceptions of workplace culture, and they shared their thoughts on stress management and professional well-being. Positive workplace practice was highlighted, and the participants revealed an environment they were proud to be a part of. Individual interviews, focus groups, and reflective practice were all used to collect data. The findings from the investigation unanimously support current literature that clearly confirms mental health nursing to be stressful. Interestingly, however, the findings also clearly identified that the way in which the nurse participants managed their stress was intrinsically linked to their job satisfaction. The major theme identified throughout the present study revealed that the female participants' ability to manage an at times complex workspace through the notions of teamwork, diversity, and creativity. All of the participants considered these elements as significant to providing a high standard in patient care. This research might provide an opportunity for others to view mental health nursing from a different perspective, and through the lived experiences of the participants, embrace the positive and rewarding aspects of the role.
An Architecture for Layering and Integration of Learning Ontologies, Applied to Personal Learning Environments and Cloud Learning Environments

Extensible Personal Learning Environments (PLEs) and Cloud Learning Environments (CLEs) that facilitate the lone or collaborative study of user-chosen blends of content and courses from heterogeneous sources, including Open Educational Resources (OERs), are gradually gaining ground in the landscape of distance learning. In this paper, we examine the use of ontologies for modelling and supporting learner activities within a PLE or CLE that draws upon sources whose ontologies may vary a lot. In particular, we propose an architecture for layering and integration of learning ontologies modelling various aspects of the learning process and facilitating the production of recommendations to learners.
Every Filter Extracts A Specific Texture In Convolutional Neural Networks

Many works have concentrated on visualizing and understanding the inner mechanism of convolutional neural networks (CNNs) by generating images that activate some specific neurons, which is called deep visualization. However, it is still unclear what the filters extract from images intuitively. In this paper, we propose a modified code inversion algorithm, called feature map inversion, to understand the function of filter of interest in CNNs. We reveal that every filter extracts a specific texture. The texture from higher layer contains more colours and more intricate structures. We also demonstrate that style of images could be a combination of these texture primitives. Two methods are proposed to reallocate energy distribution of feature maps randomly and purposefully. Then, we inverse the modified code and generate images of diverse styles. With these results, we provide an explanation about why Gram matrix of feature maps [1] could represent image style.
Altered resting brain connectivity in persistent cancer related fatigue

There is an estimated 3 million women in the US living as breast cancer survivors and persistent cancer related fatigue (PCRF) disrupts the lives of an estimated 30% of these women. PCRF is associated with decreased quality of life, decreased sleep quality, impaired cognition and depression. The mechanisms of cancer related fatigue are not well understood; however, preliminary findings indicate dysfunctional activity in the brain as a potential factor. Here we investigate the relationship between PCRF on intrinsic resting state connectivity in this population. Twenty-three age matched breast cancer survivors (15 fatigued and 8 non-fatigued) who completed all cancer-related treatments at least 12 weeks prior to the study, were recruited to undergo functional connectivity magnetic resonance imaging (fcMRI). Intrinsic resting state networks were examined with both seed based and independent component analysis methods. Comparisons of brain connectivity patterns between groups as well as correlations with self-reported fatigue symptoms were performed. Fatigued patients displayed greater left inferior parietal lobule to superior frontal gyrus connectivity as compared to non-fatigued patients (P < 0.05 FDR corrected). This enhanced connectivity was associated with increased physical fatigue (P = 0.04, r = 0.52) and poor sleep quality (P = 0.04, r = 0.52) in the fatigued group. In contrast greater connectivity in the non-fatigued group was found between the right precuneus to the periaqueductal gray as well as the left IPL to subgenual cortex (P < 0.05 FDR corrected). Mental fatigue scores were associated with greater default mode network (DMN) connectivity to the superior frontal gyrus (P = 0.05 FDR corrected) among fatigued subjects (r = 0.82) and less connectivity in the non-fatigued group (r = -0.88). These findings indicate that there is enhanced intrinsic DMN connectivity to the frontal gyrus in breast cancer survivors with persistent fatigue. As the DMN is a network involved in self-referential thinking we speculate that enhanced connectivity between the DMN and the frontal gyrus may be related to mental fatigue and poor sleep quality. In contrast, enhanced connectivity between the DMN and regions in the subgenual cingulate and brainstem may serve a protective function in the non-fatigued group.
A TRIZ-Based Method for New Service Design

This article demonstrates the viability of applying the theory of inventive problem solving (TRIZ) to services by proposing a new approach to new service design. Traditionally, the effectiveness of new service design is unpredictable as service design relies largely on inspiration and the past experiences of service designers. By integrating TRIZ problem-solving tools and its knowledge base, the authors propose a new TRIZ-based approach to address this weakness in service design. Through two case studies, the proposed model is verified. This demonstrates the relevance of TRIZ to service design. It is hoped that this article will raise awareness among service researchers so that more studies in this direction are conducted.
Synthesis, characterization, antibiogram and DNA binding studies of novel Co(II), Ni(II), Cu(II), and Zn(II) complexes of Schiff base ligands with quinoline core

A series of Co(II), Ni(II), Cu(II), and Zn(II) complexes of Schiff base ligands L1H3 and L2H have been prepared. The ligands are synthesized by the condensation of 2-hydroxy-3-formylquinoline with salicyloylhydrazide and 2-hydrazinobenzothiazole in absolute ethanol. The prepared complexes were characterized by the analytical and spectral techniques. The stoichiometry of the complexes is found to be 1:1. The presence of coordinated and lattice water is confirmed by the TG and DTA studies. Subsequently all the prepared complexes were screened for antimicrobial activity against bacteria and fungi. The Cu(II) complexes have been found to be more active than the ligand. In addition the DNA binding/cleaving capacity of the compounds was analyzed by absorption spectroscopy, viscosity measurement, thermal denaturation, and gel electrophoresis methods.