bluuebunny/crossref_metadata_2025_split huggingface dataset:
Mass-wasting processes along the margins of the Ulleung Basin, East Sea: insights from multichannel seismic reflection and multibeam echosounder data
Authors: Horozal Senay , Bahk Jang-Jun , Lee Sang Hoon , Cukur Deniz , Urgeles Roger , Kim Gil Young , Kim Seong-Pil , Ryu Byong-Jae , Kim Jin-Ho 
Published: April 2018

Abstract

Submarine landslides represent a major, previously little recognized, geological hazard to the coastal communities. This study investigates the size, depth and degree of submarine landslides along the margins of the Ulleung Basin and examines how the shelf morphology and sediment supply affect the style and occurrence of slope failures. The slopes have experienced at least 38 episodes of submarine failures, which have left clear arcuate-shaped scarps that initiate at water depths of 150–1120 m. Individual landslides comprise volumes over the range 0.1–340 km
3
, cover 20–800 km
2
on the seafloor and have runout distances of up to 50 km from the source. The headwall scarps are observed as being in excess of 500 m high. The height of scarps in the southern margin is significantly larger than in the western margin. Moreover, the volume of mass-transport deposits in the southern margin is also much higher compared to those from the western margin. The occurrence of the broad shelf (30–150 km wide) and high sedimentation rates in the southern margin might have led to large-scale slope failures. In contrast, the narrow shelf (<20 km) and low sedimentation rates in the western margin would only have promoted small-scale mass-wasting events.
Sentence Relations for Extractive Summarization with Deep Neural Networks
Authors: Ren Pengjie , Chen Zhumin , Ren Zhaochun , Wei Furu , Nie Liqiang , Ma Jun , de Rijke Maarten 
Published: April 2018

Sentence regression is a type of extractive summarization that achieves state-of-the-art performance and is commonly used in practical systems. The most challenging task within the sentence regression framework is to identify discriminative features to represent each sentence. In this article, we study the use of sentence relations, e.g., Contextual Sentence Relations (CSR), Title Sentence Relations (TSR), and Query Sentence Relations (QSR), so as to improve the performance of sentence regression. CSR, TSR, and QSR refer to the relations between a main body sentence and its local context, its document title, and a given query, respectively.
We propose a deep neural network model, Sentence Relation-based Summarization (SRSum), that consists of five sub-models, PriorSum, CSRSum, TSRSum, QSRSum, and SFSum. PriorSum encodes the latent semantic meaning of a sentence using a bi-gram convolutional neural network. SFSum encodes the surface information of a sentence, e.g., sentence length, sentence position, and so on. CSRSum, TSRSum, and QSRSum are three sentence relation sub-models corresponding to CSR, TSR, and QSR, respectively. CSRSum evaluates the ability of each sentence to summarize its local contexts. Specifically, CSRSum applies a CSR-based word-level and sentence-level attention mechanism to simulate the context-aware reading of a human reader, where words and sentences that have anaphoric relations or local summarization abilities are easily remembered and paid attention to. TSRSum evaluates the semantic closeness of each sentence with respect to its title, which usually reflects the main ideas of a document. TSRSum applies a TSR-based attention mechanism to simulate people’s reading ability with the main idea (title) in mind. QSRSum evaluates the relevance of each sentence with given queries for the query-focused summarization. QSRSum applies a QSR-based attention mechanism to simulate the attentive reading of a human reader with some queries in mind. The mechanism can recognize which parts of the given queries are more likely answered by a sentence under consideration. Finally as a whole, SRSum automatically learns useful latent features by jointly learning representations of query sentences, content sentences, and title sentences as well as their relations.
We conduct extensive experiments on six benchmark datasets, including generic multi-document summarization and query-focused multi-document summarization. On both tasks, SRSum achieves comparable or superior performance compared with state-of-the-art approaches in terms of multiple ROUGE metrics.
Local Fast Failover Routing With Low Stretch
Authors: Foerster Klaus-Tycho , Pignolet Yvonne-Anne , Schmid Stefan , Tredan Gilles 
Published: April 2018

Network failures are frequent and disruptive, and can significantly reduce the throughput even in highly connected and regular networks such as datacenters. While many modern networks support some kind of local fast failover to quickly reroute flows encountering link failures to new paths, employing such mechanisms is known to be non-trivial, as conditional failover rules can only depend on local failure information.
While over the last years, important insights have been gained on how to design failover schemes providing high resiliency, existing approaches have the shortcoming that the resulting failover routes may be unnecessarily long, i.e., they have a large stretch compared to the original route length. This is a serious drawback, as long routes entail higher latencies and introduce loads, which may cause the rerouted flows to interfere with existing flows and harm throughput.
This paper presents the first deterministic local fast failover algorithms providing provable resiliency and failover route lengths, even in the presence of many concurrent failures. We present stretch-optimal failover algorithms for different network topologies, including multi-dimensional grids, hypercubes and Clos networks, as they are frequently deployed in the context of HPC clusters and datacenters. We show that the computed failover routes are optimal in the sense that no failover algorithm can provide shorter paths for a given number of link failures.
A Scalable VPN Gateway for Multi-Tenant Cloud Services
Authors: Arashloo Mina Tahmasbi , Shirshov Pavel , Gandhi Rohan , Lu Guohan , Yuan Lihua , Rexford Jennifer 
Published: April 2018

Major cloud providers offer networks of virtual machines with private IP addresses as a service on the cloud. To isolate the address space of different customers, customers are required to tunnel their traffic to a Virtual Private Network (VPN) gateway, which is typically a middlebox inside the cloud that internally tunnels each packet to the correct destination. To improve performance, an increasing number of enterprises connect directly to the cloud provider's network at the edge, to a device we call the provider's edge (PE). PE is a chokepoint for customer's traffic to the cloud, and therefore a natural candidate for implementing network functions concerning customers' virtual networks, including the VPN gateway, to avoid a detour to middleboxes inside the cloud.
At the scale of today's cloud providers, VPN gateways need to maintain information for around a million internal tunnels. We argue that no single commodity device can handle these many tunnels while providing a high enough port density to connect to hundreds of cloud customers at the edge. Thus, in this paper, we propose a hybrid architecture for the PE, consisting of a commodity switch, connected to a commodity server which uses Data-Plane Development Kit (DPDK) for fast packet processing. This architecture enables a variety of network functions at the edge by offering the benefits of both hardware and software data planes. We implement a scalable VPN gateway on our proposed PE and show that it matches the scale requirements of today's cloud providers while processing packets close to line rate.
Novel Effector Phenotype of Tim-3+ Regulatory T Cells Leads to Enhanced Suppressive Function in Head and Neck Cancer Patients
Authors: Liu Zhuqing , McMichael Elizabeth L. , Shayan Gulidanna , Li Jing , Chen Kevin , Srivastava Raghvendra , Kane Lawrence P. , Lu Binfeng , Ferris Robert L. 
Published: April 2018

Abstract
Purpose: Regulatory T (Treg) cells are important suppressive cells among tumor-infiltrating lymphocytes (TIL). Treg cells express the well-known immune checkpoint receptor PD-1, which is reported to mark “exhausted” Treg with lower suppressive function. T-cell immunoglobulin mucin (Tim)-3, a negative regulator of Th1 immunity, is expressed by a sizeable fraction of TIL Tregs, but the functional status of Tim-3+ Tregs remains unclear.
Experimental Design: CD4+CTLA-4+CD25high Treg cells were sorted from freshly excised head and neck squamous cell carcinoma (HNSCC) TIL based on Tim-3 expression. Functional and phenotypic features of these Tim-3+ and Tim-3− TIL Tregs were tested by in vitro suppression assays and multi-color flow cytometry. Gene-expression profiling and NanoString analysis of Tim-3+ TIL Treg were performed. A murine HNSCC tumor model was used to test the effect of anti-PD-1 immunotherapy on Tim-3+ Treg.
Results: Despite high PD-1 expression, Tim-3+ TIL Treg displayed a greater capacity to inhibit naïve T-cell proliferation than Tim-3− Treg. Tim-3+ Treg from human HNSCC TIL also displayed an effector-like phenotype, with more robust expression of CTLA-4, PD-1, CD39, and IFN-γ receptor. Exogenous IFN-γ treatment could partially reverse the suppressive function of Tim-3+ TIL Treg. Anti-PD-1 immunotherapy downregulated Tim-3 expression on Tregs isolated from murine HNSCC tumors, and this treatment reversed the suppressive function of HNSCC TIL Tregs.
Conclusions: Tim-3+ Treg are functionally and phenotypically distinct in HNSCC TIL, and are highly effective at inhibiting T-cell proliferation despite high PD-1 expression. IFN-γ induced by anti–PD-1 immunotherapy may be beneficial by reversing Tim-3+ Treg suppression. Clin Cancer Res; 24(18); 4529–38. ©2018 AACR.
Cross-talk between T Cells and Hematopoietic Stem Cells during Adoptive Cellular Therapy for Malignant Glioma
Authors: Wildes Tyler J. , Grippin Adam , Dyson Kyle A. , Wummer Brandon M. , Damiani David J. , Abraham Rebecca S. , Flores Catherine T. , Mitchell Duane A. 
Published: April 2018

AbstractPurpose: Adoptive T-cell immunotherapy (ACT) has emerged as a viable therapeutic for peripheral and central nervous system (CNS) tumors. In peripheral cancers, optimal efficacy of ACT is reliant on dendritic cells (DCs) in the tumor microenvironment. However, the CNS is largely devoid of resident migratory DCs to function as antigen-presenting cells during immunotherapy. Herein, we demonstrate that cellular interactions between adoptively transferred tumor-reactive T cells and bone marrow–derived hematopoietic stem and progenitor cells (HSPCs) lead to the generation of potent intratumoral DCs within the CNS compartment.Experimental Design: We evaluated HSPC differentiation during ACT in vivo in glioma-bearing hosts and HSPC proliferation and differentiation in vitro using a T-cell coculture system. We utilized FACS, ELISAs, and gene expression profiling to study the phenotype and function of HSPC-derived cells ex vivo and in vivo. To demonstrate the impact of HSPC differentiation and function on antitumor efficacy, we performed survival experiments.Results: Transfer of HSPCs with concomitant ACT led to the production of activated CD86+CD11c+MHCII+ cells consistent with DC phenotype and function within the brain tumor microenvironment. These intratumoral DCs largely supplanted abundant host myeloid-derived suppressor cells. We determined that during ACT, HSPC-derived cells in gliomas rely on T-cell–released IFNγ to differentiate into DCs, activate T cells, and reject intracranial tumors.Conclusions: Our data support the use of HSPCs as a novel cellular therapy. Although DC vaccines induce robust immune responses in the periphery, our data demonstrate that HSPC transfer uniquely generates intratumoral DCs that potentiate T-cell responses and promote glioma rejection in situ. Clin Cancer Res; 24(16); 3955–66. ©2018 AACR.
Intraoperative Resection Guidance with Photoacoustic and Fluorescence Molecular Imaging Using an Anti–B7-H3 Antibody-Indocyanine Green Dual Contrast Agent
Authors: Wilson Katheryne E. , Bachawal Sunitha V. , Willmann Jürgen K. 
Published: April 2018

Abstract
Purpose: Breast cancer often requires surgical treatment including breast-conserving surgical resection. However, with current postsurgical histologic margin analysis, one quarter of breast cancer patients undergo reexcision to achieve negative margins corresponding to decreased local recurrence and better outcomes. Therefore, a method with high resolution and specificity for intraoperative margin assessment is needed.
Experimental Design: First, quantitative immunofluorescence staining of B7-H3 expression was assessed in four pathologic stages of breast cancer progression of the MMTV-PyMT transgenic murine model. Next, an antibody–dye contrast agent, B7-H3-ICG, was injected into mice prior to surgical resection of breast cancer. Anatomic ultrasound, spectroscopic photoacoustic (sPA), and fluorescence imaging were used to guide resection of mammary glands suspected of containing cancer. Resected tissues were processed for H&E staining and pathologic assessment and compared with sPA and fluorescence imaging signals.
Results: Tissue containing DCIS (46.0 ± 4.8 a.u.) or invasive carcinoma (91.7 ± 21.4 a.u.) showed significantly higher (P &lt; 0.05) B7-H3 expression than normal and hyperplastic tissues (1.3 ± 0.8 a.u.). During image-guided surgical resection, tissue pieces assessed as normal or hyperplastic (n = 17) showed lower average sPA (3.17 ± 0.48 a.u.) and fluorescence signal [6.83E07 ± 2.00E06 (p/s)/(μW/cm²)] than DCIS and invasive carcinoma tissue (n = 63) with an average sPA signal of 23.98 ± 4.88 a.u. and an average fluorescence signal of 7.56E07 ± 1.44E06 (p/s)/(μW/cm²) with AUCs of 0.93 [95% confidence interval (CI), 0.87–0.99] and 0.71 (95% CI, 0.57–0.85), respectively.
Conclusions: It was demonstrated that sPA and fluorescence molecular imaging combined with B7-H3-ICG agent can assess the disease status of tissues with high diagnostic accuracy, intraoperatively, with high resolution, sensitivity, and specificity. Clin Cancer Res; 24(15); 3572–82. ©2018 AACR.
Low Levels of Caveolin-1 Predict Symptomatic Bleeding After Thrombolytic Therapy in Patients With Acute Ischemic Stroke
Authors: Castellanos Mar , van Eendenburg Cecile , Gubern Carme , Kádár Elisabet , Huguet Gemma , Puig Josep , Sobrino Tomás , Blasco Gerard , Serena Joaquín , Sánchez Juan Manuel 
Published: April 2018

Background and Purpose—
Experimental models of cerebral ischemia demonstrate that the decrease in the caveolin-1 membrane protein results in an increase in endothelial permeability. Because this phenomenon is responsible for hemorrhagic transformation (HT) after cerebral ischemia, we aimed to determine whether caveolin-1 levels may predict bleeding after recombinant tissue-type plasminogen activator (r-tPA) administration in patients with acute stroke.

Methods—
We studied 133 patients with a first hemispheric stroke treated with r-tPA within 4.5 hours of symptom onset. HT was evaluated and classified on cranial computed tomography at 24 hours and was considered as symptomatic HT (sHT) if associated with neurological deterioration. Serum caveolin-1 levels were analyzed before and at 2, 24, and 72 hours post–r-tPA administration in patients and in 40 healthy controls.

Results—

Baseline caveolin-1 levels were higher in patients than controls (0.24 [0.17–0.40] versus 0.07 [0.0–0.20] ng/mL;
P
<0.000). Twenty six (19.5%) patients had HT, which was symptomatic in 7 (5.3%). Patients with parenchymal hemorrhage-2 and sHT had lower baseline caveolin-1 levels than the rest of patients (0.08 [0.04–0.19] versus 0.26 [0.14–0.40];
P
=0.019 and 0.08 [0.02–0.17] versus 0.26 [0.13–0.41];
P
=0.019, respectively). The levels remained stable in the first 72 hours in patients with parenchymal hemorrhage-2 and sHT, whereas in the rest of patients levels decreased in this time. Caveolin-1 levels ≤0.17 ng/mL had the highest predictive capacity of sHT (86% sensitivity, 65% specificity, 99% negative predictive value, 12% positive predictive value). After adjustment for confounders, caveolin-1 levels ≤0.17 ng/mL independently predicted sHT (odds ratio, 11.6; 95% confidence interval, 11.3–102.8;
P
=0.027).

Conclusions—
Low serum levels of caveolin-1 are an independent predictor of sHT after r-tPA administration. Because of the small sample size, further research is needed to validate these data.
Day-ahead forecasting of grid carbon intensity in support of heating, ventilation and air-conditioning plant demand response decision-making to reduce carbon emissions
Authors: Lowry Gordon 
Published: April 2018

Electrical heating, ventilation and air-conditioning loads in buildings are suitable candidates for use in demand response activity. This paper demonstrates a method to support planned demand response actions intended explicitly to reduce carbon emissions. Demand response is conventionally adopted to aid the operation of electricity grids and can lead to greater efficiency; here it is planned to target times of day when electricity is generated with high carbon intensity. Operators of heating, ventilation and air-conditioning plant and occupants of conditioned spaces can plan when to arrange shutdown of plant once they can foresee the opportune time of day for carbon saving. It is shown that the carbon intensity of the mainland UK electricity grid varies markedly throughout the day, but that this tends to follow daily and weekly seasonal patterns. To enable planning of demand response, 24 h ahead forecast models of grid carbon intensity are developed that are not dependent on collecting multiple exogenous data sets. In forecasting half-hour periods of high carbon intensity either linear autoregressive or non-linear artificial neural network models can be used, but a daily seasonal autoregressive model is shown to provide a 20% improvement in carbon reduction. Practical application: The forecast method demonstrated in the paper would enable building operators to plan demand response activity to target times of high carbon intensity on the UK electricity grid. The method would be easy to implement as the only data required are publicly available.
The difficulties of discharging hospice patients to care homes at the end of life: A focus group study
Authors: Thomas Tabitha , Clarke Gemma , Barclay Stephen 
Published: April 2018

Background: Discharge from inpatient palliative care units to long-term care can be challenging. In the United Kingdom, hospice inpatients move to a care home if they no longer require specialist palliative care and cannot be discharged home. There is evidence to suggest that patients and families find the prospect of such a move distressing. Aim: To investigate the issues that arise when patients are transferred from hospice to care home at the end of life, from the perspective of the hospice multidisciplinary team. Design: A qualitative study, using thematic analysis to formulate themes from focus group discussions with hospice staff. Setting/participants: Five focus groups were conducted with staff at five UK hospices. Participants included multidisciplinary team members involved in discharge decisions. All groups had representation from a senior nurse and doctor at the hospice, with group size between three and eight participants. All but one group included physiotherapists, occupational therapists and family support workers. Results: A major focus of group discussions concerned dilemmas around discharge. These included (1) ethical concerns (dilemmas around the decision, lack of patient autonomy and allocation of resources); (2) communication challenges; and (3) discrepancies between the ideals and realities of hospice palliative care. Conclusion: Hospice palliative care unit staff find discharging patients to care homes necessary, but often unsatisfactory for themselves and distressing for patients and relatives. Further research is needed to understand patients’ experiences concerning moving to care homes for end of life care, in order that interventions can be implemented to mitigate this distress.
Textbook descriptions of people with psychosis – some ethical aspects
Authors: Fredwall Terje Emil , Larsen Inger Beate 
Published: April 2018

Background: Textbooks are central for the education of professionals in the health field and a resource for practitioners already in the field. Objectives: This article focuses on how 12 textbooks in psychiatric nursing and psychiatry, published in Norway between 1877 and 2012, describe and present people with psychosis. Research design: We used qualitative content analysis. Ethical considerations: The topic is published textbooks, made available to be read by students, teachers and professionals, and no ethical approval was required. Findings: The analysis shows that all 12 textbooks describe and present people who are considered as psychotic from a ‘perspective from above’. In this perspective, the readers are learning about psychosis in the professional’s language and from the author’s viewpoint. Most often the textbooks communicate a universal image of people with psychosis, a description that fits with the diagnostic criteria. The analysis also shows that two textbooks in psychiatric nursing combined this perspective with a ‘perspective from within’. Here, the readers are learning about psychosis from the patients’ own viewpoint. The authors communicate a personal, psychotic universe that differs from various people, even if they have the same diagnosis, and the descriptions are focusing on the patient as a whole person. Discussion and conclusion: Drawing partly on Rita Charon’s writings about narrative knowledge in the health field, and partly on insights from Martha Nussbaum and her concept of narrative imagination, we argue that mental health professionals need to learn about, understand and fathom what patients go through by reading, listening to and acknowledging the patients’ own stories and experiences. Cultivating the capacity for empathy and compassion are at the very heart of moral performance in the mental health field. A valuable moral resource in that regard is leading textbooks and how they describe and present people with severe mental illness.
High expression of Aurora-B is correlated with poor prognosis and drug resistance in non-small cell lung cancer
Authors: Yu JingJing , Zhou Jing , Xu Fei , Bai Wei , Zhang Wei 
Published: April 2018

Objective: Aurora kinase B (Aurora-B) is a crucial regulator of accurate mitosis. Abnormal Aurora-B expression is associated with aneuploidy and has been implicated in the pathogenesis and drug resistance in a variety of human cancers. However, little evidence is available regarding the role of Aurora-B in regulating drug response in non-small cell lung cancer (NSCLC), which is the most common type of lung cancer, and is characterized with poor prognosis and high mortality. Method: In the current study, we investigated the association of Aurora-B with the prognosis of NSCLC patients, and we also used the latest CRISPR/Cas9 system to explore the regulatory role of Aurora-B in NSCLC cells developing resistance to cisplatin (CDDP) and paclitaxel. Results: We found that Aurora-B was correlated with significantly reduced overall survival and disease-free survival in NSCLC patients. Aurora-B overexpression was also observed in NSCLC cells developing impaired response to both CDDP and paclitaxel. Moreover, we found, for the first time, that Aurora-B may impair NSCLC drug response by disturbing cell proliferation and inhibiting p53-related DNA damage response and apoptotic pathway, while the knockout of Aurora-B resensitized NSCLC cells to chemo drugs by ensuring correct chromosome segregation and restoring p53 expression. Conclusions: Our results demonstrated the association of Aurora-B with chemoresistance in NSCLC, which may finally contribute to the poor prognosis of NSCLC patients. We also suggested Aurora-B as a promising therapeutic target in NSCLC treatment.