Miracle-dz/UniFAR-FTUs huggingface dataset:
Interdisciplinary Diagnosis, Therapy and Follow-up of Patients with Endometrial Cancer. Guideline (S3-Level, AWMF Registry Nummer 032/034-OL, April 2018) – Part 1 with Recommendations on the Epidemiology, Screening, Diagnosis and Hereditary Factors of Endometrial Cancer

Summary The first German interdisciplinary S3-guideline on the diagnosis, therapy and follow-up of patients with endometrial cancer was published in April 2018. Funded by German Cancer Aid as part of an Oncology Guidelines Program, the lead coordinators of the guideline were the German Society of Gynecology and Obstetrics (DGGG) and the Gynecological Oncology Working Group (AGO) of the German Cancer Society (DKG). Purpose The use of evidence-based, risk-adapted therapy to treat low-risk women with endometrial cancer avoids unnecessarily radical surgery and non-useful adjuvant radiotherapy and/or chemotherapy. This can significantly reduce therapy-induced morbidity and improve the patientʼs quality of life as well as avoiding unnecessary costs. For women with endometrial cancer and a high risk of recurrence, the guideline defines the optimal surgical radicality together with the appropriate chemotherapy and/or adjuvant radiotherapy where required. The evidence-based optimal use of different therapeutic modalities should improve survival rates and the quality of life of these patients. The S3-guideline on endometrial cancer is intended as a basis for certified gynecological cancer centers. The aim is that the quality indicators established in this guideline will be incorporated in the certification processes of these centers. Methods The guideline was compiled in accordance with the requirements for S3-level guidelines. This includes, in the first instance, the adaptation of source guidelines selected using the DELBI instrument for appraising guidelines. Other consulted sources include reviews of evidence which were compiled from literature selected during systematic searches of literature databases using the PICO scheme. In addition, an external biostatistics institute was commissioned to carry out a systematic search and assessment of the literature for one area of the guideline. The identified materials were used by the interdisciplinary working groups to develop suggestions for Recommendations and Statements, which were then modified during structured consensus conferences and/or additionally amended online using the DELPHI method with consent being reached online. The guideline report is freely available online. Recommendations Part 1 of this short version of the guideline presents recommendations on epidemiology, screening, diagnosis and hereditary factors, The epidemiology of endometrial cancer and the risk factors for developing endomentrial cancer are presented. The options for screening and the methods used to diagnose endometrial cancer including the pathology of the cancer are outlined. Recommendations are given for the prevention, diagnosis, and therapy of hereditary forms of endometrial cancer.
Audience Evaluation and Biometric Technology: Challenges and Opportunities

Evaluating the audience experience for performing arts events is notoriously challenging. Yet proving the impact of arts events is increasingly important, particularly when seeking to apply for much needed government and philanthropic funding. Researchers in the field of affective computing have turned to biometric technology to gather vital data on the audience experience in a rigorous and robust manner. Unfortunately, arts researchers have been more reluctant to use such technology for audience evaluations. This paper reviews the literature on audience evaluations, with a focus on how biometric technology is being used to capture the audience experience. This review highlights a gap in existing methodologies and makes a case for the use of Facial Recognition Technology to be explored and further developed, in order to gather important information on an audience’s emotional reactions to the performing arts events, as well as their demographic characteristics.
The effects of perceived health status on privacy concerns and opt-in intention toward Health Information Exchanges (HIEs)

Literature has highlighted that sensitivity of health information, which is shared through health information exchanges (HIEs), has caused security and privacy concerns. However, little is known about how perceived health status can affect patients’ privacy concerns and opt-in intentions toward HIEs. The interaction of perceived health status and privacy concerns may significantly affect the national adoption of HIEs by consumers and the widespread diffusion of electronic exchange models by healthcare organizations in the future. To investigate the role of health status in the adoption equation, we conducted an online survey in the United States using 826 samples. The result shows that patients’ opt-in decision is significantly driven by concern for information privacy and the perceived health status moderates this relationship. Interestingly, on the contrary to our hypothesis, individuals who perceive themselves unhealthy are less likely to consider negative effects of concern for information privacy in their tendency to opt-in toward HIEs.
Can Information Security Awarness Mitigate Resistance Towards Patients Healthcare Portals?

Resistance behaviors toward newly implemented technology are generally predicted by the perceptions of threats associated with the use of the technology. Recent studies of resistance towards Health Information Technology (HIT) revealed users describing the fear of losing private data due to potential cyber-attacks as an important perceived threat. This study is underpinned by concepts of the information security policy compliance theory. It aims to investigate the impact information security awareness can have on mitigating HIT resistance. Precisely, it evaluates patient’s behavior towards a new Patient Portal System (PPS) after enforcing a new cyber risk management insurance policy. This work contributes to the underdeveloped area of research concerned with patients’ interactions with HIT, as well as to practice by providing important insights about the impact of information security awareness on mitigating patients’ threats from the PPS.
Marek’s Disease Virus Activates the PI3K/Akt Pathway Through Interaction of Its Protein Meq With the P85 Subunit of PI3K to Promote Viral Replication

It is known that viruses can active the phosphatidylinositol 3-kinase (PI3K)/Akt signaling pathway in host cells to support cell survival and viral replication; however, the role of PI3K/Akt signaling in the pathogenic mechanisms induced by Marek’s disease virus (MDV) which causes a neoplastic Marek’s disease in poultry, remains unknown. In this study, we showed that MDV activated the PI3K/Akt pathway in chicken embryo fibroblasts (CEFs) at the early phase of infection, whereas treatment with a PI3K inhibitor LY294002 prior to MDV infection decreased viral replication and DNA synthesis. Flow cytometry analysis showed that inhibition of the PI3K/Akt pathway could significantly increase apoptosis in MDV-infected host cells, indicating that activation of PI3K/Akt signaling could facilitate viral replication through support of cell survival during infection. Evaluation of the underlying molecular mechanism by co-immunoprecipitation and laser confocal microscopy revealed that a viral protein Meq interacted with both p85α and p85β regulatory subunits of PI3K and could induce PI3K/Akt signaling in Meq-overexpressing chicken fibroblasts. Our results showed, for the first time, that MDV activated PI3K/Akt signaling in host cells through interaction of its Meq protein with the regulatory p85 subunit of PI3K to delay cell apoptosis and promote viral replication. This study provides clues for further studies of the molecular mechanisms underlying MDV infection and pathogenicity for the host.
Genotypic and Phenotypic Characterization of IncX3 Plasmid Carrying blaNDM-7 in Escherichia coli Sequence Type 167 Isolated From a Patient With Urinary Tract Infection

Infections due to New Delhi metallo-beta lactamase (NDM)-7-producing Escherichia coli are infrequent and sporadic. In this study, we report one case of recurrent urinary tract infection caused by blaNDM-7-producing E. coli belonging to phylogenetic group A, sequence type (ST) 167. In this study, we aimed to describe the genotype and phenotype of blaNDM-7-producing E. coli in China. The isolate exhibited resistance to β-lactam antimicrobials, trimethoprim-sulfamethoxazole, quinolones, and aminoglycosides. blaNDM-7 is located on a conjugative plasmid designated pJN05NDM-7 belonging to type IncX3. pJN05NDM-7 was fully sequenced and compared with all publicly available blaNDM-7-harboring plasmids. pJN05NDM-7 is almost identical to pKpN01-NDM7 and pKW53T, although the plasmids are geographically unrelated. The comparison of IncX3 plasmids harboring blaNDM in China showed high similarity, with genetic differences within insertion fragments. Notably, the differences in plasmids of animal and human origin were insignificant, because only one plasmid showed deletion inside the ISAba125 region compared with pJN05NDM7. Our study demonstrates that E. coli carrying IncX3 plasmids play an important role as a reservoir and in the spread of blaNDM. Further studies should be performed to control the dissemination of blaNDM among food animals.
Intravitreal AAV-Delivery of Genetically Encoded Sensors Enabling Simultaneous Two-Photon Imaging and Electrophysiology of Optic Nerve Axons

Myelination of axons by oligodendrocytes is a key feature of the remarkably fast operating CNS. Oligodendrocytes not only tune axonal conduction speed but are also suggested to maintain long-term axonal integrity by providing metabolic support to the axons they ensheath. However, how myelinating oligodendrocytes impact axonal energy homeostasis remains poorly understood and difficult to investigate. Here, we provide a method of how to study electrically active myelinated axons expressing genetically encoded sensors by combining electrophysiology and two-photon imaging of acutely isolated optic nerves. We show that intravitreal adeno-associated viral (AAV) vector delivery is an efficient tool to achieve functional sensor expression in optic nerve axons, which is demonstrated by measuring axonal ATP dynamics following AAV-mediated sensor expression. This novel approach allows for fast expression of any optical sensor of interest to be studied in optic nerve axons without the need to go through the laborious process of producing new transgenic mouse lines. Viral-mediated biosensor expression in myelinated axons and the subsequent combination of nerve recordings and sensor imaging outlines a powerful method to investigate oligodendroglial support functions and to further interrogate cellular mechanisms governing axonal energy homeostasis under physiological and pathological conditions.
Unsupervised Learning of Shape and Pose with Differentiable Point Clouds

We address the problem of learning accurate 3D shape and camera pose from a collection of unlabeled category-specific images. We train a convolutional network to predict both the shape and the pose from a single image by minimizing the reprojection error: given several views of an object, the projections of the predicted shapes to the predicted camera poses should match the provided views. To deal with pose ambiguity, we introduce an ensemble of pose predictors which we then distill to a single "student" model. To allow for efficient learning of high-fidelity shapes, we represent the shapes by point clouds and devise a formulation allowing for differentiable projection of these. Our experiments show that the distilled ensemble of pose predictors learns to estimate the pose accurately, while the point cloud representation allows to predict detailed shape models. The supplementary video can be found at this https URL
Learning to Measure Change: Fully Convolutional Siamese Metric Networks for Scene Change Detection

A critical challenge problem of scene change detection is that noisy changes generated by varying illumination, shadows and camera viewpoint make variances of a scene difficult to define and measure since the noisy changes and semantic ones are entangled. Following the intuitive idea of detecting changes by directly comparing dissimilarities between a pair of features, we propose a novel fully Convolutional siamese metric Network(CosimNet) to measure changes by customizing implicit metrics. To learn more discriminative metrics, we utilize contrastive loss to reduce the distance between the unchanged feature pairs and to enlarge the distance between the changed feature pairs. Specifically, to address the issue of large viewpoint differences, we propose Thresholded Contrastive Loss (TCL) with a more tolerant strategy to punish noisy changes. We demonstrate the effectiveness of the proposed approach with experiments on three challenging datasets: CDnet, PCD2015, and VL-CMU-CD. Our approach is robust to lots of challenging conditions, such as illumination changes, large viewpoint difference caused by camera motion and zooming. In addition, we incorporate the distance metric into the segmentation framework and validate the effectiveness through visualization of change maps and feature distribution. The source code is available at this https URL.
Sequential Context Encoding for Duplicate Removal

Duplicate removal is a critical step to accomplish a reasonable amount of predictions in prevalent proposal-based object detection frameworks. Albeit simple and effective, most previous algorithms utilize a greedy process without making sufficient use of properties of input data. In this work, we design a new two-stage framework to effectively select the appropriate proposal candidate for each object. The first stage suppresses most of easy negative object proposals, while the second stage selects true positives in the reduced proposal set. These two stages share the same network structure, \ie, an encoder and a decoder formed as recurrent neural networks (RNN) with global attention and context gate. The encoder scans proposal candidates in a sequential manner to capture the global context information, which is then fed to the decoder to extract optimal proposals. In our extensive experiments, the proposed method outperforms other alternatives by a large margin.
Building a Bird: Musculoskeletal Modeling and Simulation of Wing-Assisted Incline Running During Avian Ontogeny

Flapping flight is the most power-demanding mode of locomotion, associated with a suite of anatomical specializations in extant adult birds. In contrast, many developing birds use their forelimbs to negotiate environments long before acquiring “flight adaptations,” recruiting their developing wings to continuously enhance leg performance and, in some cases, fly. How does anatomical development influence these locomotor behaviors? Isolating morphological contributions to wing performance is extremely challenging using purely empirical approaches. However, musculoskeletal modeling and simulation techniques can incorporate empirical data to explicitly examine the functional consequences of changing morphology by manipulating anatomical parameters individually and estimating their effects on locomotion. To assess how ontogenetic changes in anatomy affect locomotor capacity, we combined existing empirical data on muscle morphology, skeletal kinematics, and aerodynamic force production with advanced biomechanical modeling and simulation techniques to analyze the ontogeny of pectoral limb function in a precocial ground bird (Alectoris chukar). Simulations of wing-assisted incline running (WAIR) using these newly developed musculoskeletal models collectively suggest that immature birds have excess muscle capacity and are limited more by feather morphology, possibly because feathers grow more quickly and have a different style of growth than bones and muscles. These results provide critical information about the ontogeny and evolution of avian locomotion by (i) establishing how muscular and aerodynamic forces interface with the skeletal system to generate movement in morphing juvenile birds, and (ii) providing a benchmark to inform biomechanical modeling and simulation of other locomotor behaviors, both across extant species and among extinct theropod dinosaurs.
NEW DETAILS EMERGE! Revealing the Effects of Clickbait Headlines on User Responses

This study investigates the influence of a conventional method of delivering news headlines, clickbait, on online users’ perceptions and responses. An experiment was conducted on two groups of news headlines— traditional news and clickbait—to provide empirical evidence of the effects of clickbait on online users. The findings suggest that clickbait headlines can evoke users’ arousal and curiosity. In addition, the results from structural equation modeling fill the gap in the literature by providing evidence of the factors influencing users’ intention to read and share online news. The results reveal that while the major determinant of users’ intention to read news stories is curiosity, perceived knowledge quality appears to be the main factor users consider when sharing online news stories.
Both NaCl and H2O2 Long-Term Stresses Affect Basal Cytosolic Ca2+ Levels but Only NaCl Alters Cytosolic Ca2+ Signatures in Arabidopsis

Salinity is one of the formidable environmental factors that affect plant growth and development and constrain agricultural productivity. Experimentally imposed short-term NaCl treatment triggers a transient increase in cytosolic free Ca2+ concentration ([Ca2+]i) via Ca2+ influx across the plasma membrane. Salinity stress, as well as other stresses, induces the production of reactive oxygen species (ROS), such as H2O2. It is well established that short-term H2O2 treatment also triggers a transient increase in [Ca2+]i. However, whether and how long-term NaCl and H2O2 treatments affect the basal levels of [Ca2+]i as well as plant responses to additional NaCl and H2O2 stresses remain poorly understood. Using an aequorin-based Ca2+ imaging assay, we found that the long-term treatment of Arabidopsis seedlings with both moderate NaCl and H2O2 in the growth media reduced the basal [Ca2+]i levels. Interestingly, we found that the long-term treatment with NaCl, but not H2O2, affected the responses of plants to additional NaCl stress, and remarkably the roots displayed enhanced responses while the leaves showed reduced responses. These findings suggest that plants adapt to the long-term NaCl stress, while H2O2 might be an integrator of many stresses.
Virtual Reality in Marketing: Technological and Psychological immersion

The use of virtual reality (VR) in Marketing research and practice is blooming, which suggests that Marketing can largely benefit from VR applications. In multidisciplinary applications of technology, it is important to organize the results of current studies and to define the terminology to subsidize future studies. To date, there is no literature review regarding the use of VR in all marketing applications. This paper aims to leverage future studies and practices by presenting a systematic review that covers VR immersive applications to Marketing performed by a team of Computer Science, Computer Engineering, Marketing, Psychology and Information System (IS) researchers. From over 630 papers retrieved, 59 papers were reviewed. The findings were analyzed and discussed according to the technological and psychological immersion perspectives and marketing applications. Consumer learning was the most frequent topic investigated. Most studies reported positive outcomes. Gaps and limitations were identified, and future works were suggested.
Institutional Effects on API Development and Integration in Developing Countries: Evidence from Ghana

Application Programming Interfaces (APIs) are perceived as major enablers of digital transformation, as such they have attracted the attention of both practitioners and researchers. This notwithstanding, past research on APIs have focused largely on the technical dimensions, neglecting the social and cultural contexts. The purpose of this study is therefore to understand how regulative, normative and cognitive institutions affect the development and integration of APIs in Ghana. Drawing on the new institutional theory as a lens and an interpretive case study methodology, our findings show that normative institutions such as business strategy, customers need, relationships, and experience of vendors enabled the development and integration of APIs. However, regulative institutions in the form of regulations and laws (unwillingness of some institutions to integrate with other applications), security concerns, were regarded as constraining factors to API integration. Also, Cognitive forces in the form of non-disclosure issues and carelessness constrained the integration of APIs.
The Multiple Determinants of Maternal Parenting Stress 12 Months After Birth: The Contribution of Antenatal Attachment Style, Adverse Childhood Experiences, and Infant Temperament

Parenting stress can influence caregiving behavior negatively, which in turn may harm children’s development. Identifying precursors of parenting stress, preferably beginning during pregnancy and throughout the first year of life, is therefore important. The present study aims to provide novel knowledge on this issue through a detailed examination of the association between maternal attachment style and later parenting stress. Moreover, we examine the role of several additional risk factors, specificially the mothers’ own adverse childhood experiences (ACE), as well as infants’ temperamental characteristics. Data from a community based longitudinal study of 1,036 Norwegian mothers, collected during pregnancy and 12 months after childbirth, were used. Results showed that attachment style in pregnancy predicted parenting stress 1 year after birth. In addition, it was demonstrated that the mothers’ own ACEs predicted postnatal parenting stress, and that attachment style operated as a mediator of this association. A significant association between perceived infant temperament and parenting stress was also found. The study illustrates the importance of understanding the multifactorial antecedents of parenting stress. The results may inform early intervention efforts aimed at supporting mothers and their partners in the potentially difficult transition period around childbirth.
pair2vec: Compositional Word-Pair Embeddings for Cross-Sentence Inference

Reasoning about implied relationships (e.g. paraphrastic, common sense, encyclopedic) between pairs of words is crucial for many cross-sentence inference problems. This paper proposes new methods for learning and using embeddings of word pairs that implicitly represent background knowledge about such relationships. Our pairwise embeddings are computed as a compositional function of each word’s representation, which is learned by maximizing the pointwise mutual information (PMI) with the contexts in which the the two words co-occur. We add these representations to the cross-sentence attention layer of existing inference models (e.g. BiDAF for QA, ESIM for NLI), instead of extending or replacing existing word embeddings. Experiments show a gain of 2.7% on the recently released SQuAD 2.0 and 1.3% on MultiNLI. Our representations also aid in better generalization with gains of around 6-7% on adversarial SQuAD datasets, and 8.8% on the adversarial entailment test set by Glockner et al. (2018).