bluuebunny/crossref_metadata_2025_split huggingface dataset:
The DizzyQuest: to have or not to have… a vertigo attack?
Authors: de Joode L. E. G. H. , Martin E. C. , Stultiens J. J. A. , Leue C. , Delespaul P. , Peeters F. , Erdkamp A. , van de Weijer S. , Blom H. , Bruintjes T. , Zwergal A. , Grill E. , Guinand N. , Perez-Fornos A. , van de Berg M. R. , Widdershoven J. , Kingma H. , van de Berg R. 
Published: July 2020

Abstract
Background
The DizzyQuest, an app-based vestibular diary, provides the opportunity to capture the number and nature of vertigo attacks in daily life. To accomplish this, the DizzyQuest provides different strategies: event sampling using an attack questionnaire, and time sampling using an evening questionnaire. Objective of this study was to investigate whether the number and nature of reported vertigo attacks was comparable between the two questionnaires.

Methods
Fifty-seven patients, who reported vertigo attacks, used the DizzyQuest for on average 24 days. The number and nature (including symptoms, triggers and duration) of vertigo attacks were compared between the attack and the evening questionnaire.

Results
The attack questionnaire was used 192 times. In contrast, at least 749 new vertigo attacks were reported in 446 evening questionnaires. A vertigo attack was not always reported in both questionnaires during the same day. Vertigo attacks that were most likely captured by both questionnaires were not always reported the same in both questionnaires regarding triggers and duration.

Conclusion
Event sampling using an attack questionnaire has low recall bias and, therefore, reliably captures the nature of the attack, but induces a risk of under-sampling. Time sampling using an evening questionnaire suffers from recall bias, but seems more likely to capture less discrete vertigo attacks and it facilitates registration of the absence of vertigo attacks. Depending on the clinical or research question, the right strategy should be applied and participants should be clearly instructed about the definition of a vertigo attack.
Added value of 3D-vision during robotic pancreatoduodenectomy anastomoses in biotissue (LAEBOT 3D2D): a randomized controlled cross-over trial
Authors: Zwart Maurice J. W. , Jones Leia R. , Balduzzi Alberto , Takagi Kosei , Vanlander Aude , van den Boezem Peter B. , Daams Freek , Rosman Camiel , Lips Daan J. , Moser Arthur J. , Hogg Melissa E. , Busch Olivier R. C. , Stommel Martijn W. J. , Besselink Marc G. ,   For the Dutch Pancreatic Cancer Group
Published: July 2020

Abstract
Background
We tested the added value of 3D-vision on procedure time and surgical performance during robotic pancreatoduodenectomy anastomoses in biotissue. Robotic surgery has the advantage of articulating instruments and 3D-vision. Consensus is lacking on the added value of 3D-vision during laparoscopic surgery. Given the improved dexterity with robotic surgery, the added value of 3D-vision may be even less with robotic surgery.

Methods
In this experimental randomized controlled cross-over trial, 20 surgeons and surgical residents from 5 countries performed robotic pancreaticojejunostomy and hepaticojejunostomy anastomoses in a biotissue organ model using the da Vinci® system and were randomized to start with either 3D- or 2D-vision. Primary endpoint was the time required to complete both anastomoses. Secondary endpoint was the objective structured assessment of technical skill (OSATS; range 12–60) rating; scored by two observers blinded to 3D/2D.

Results
Robotic 3D-vision reduced the combined operative time from 78.1 to 57.3 min (24.6% reduction, p < 0.001; 20.8 min reduction, 95% confidence intervals 12.8–28.8 min). This reduction was consistent for both anastomoses and between surgeons and residents, p < 0.001. Robotic 3D-vision improved OSATS performance by 6.1 points (20.8% improvement, p = 0.003) compared to 2D (39.4 to 45.1 points, ± 5.5).

Conclusion
3D-vision has a considerable added value during robotic pancreatoduodenectomy anastomoses in biotissue in both time reduction and improved surgical performance as compared to 2D-vision.
Noise modeling of offshore platform using progressive normalized distance from worst-case error for optimal neuron numbers in deep belief network
Authors: Chin Cheng Siong , Zhang Ronghui 
Published: July 2020

AbstractNoise prediction is important for crew comfort in an offshore platform such as oil drilling rig. A deep neural network learning on the oil drilling rig is not widely studied. In this paper, a deep belief network (DBN) with the last layer initialized with trained DBN (named DBN-DNN) is used to model the sound pressure level (SPL) in the compartments of the oil drilling rig. The method finds an optimal number of the hidden neurons in restricted Boltzmann machine by using a normalized Euclidean distance from the worst possible error for each hidden layer progressively. The dataset used for experimental results is obtained via vibroacoustics simulation software such as VA-One and actual site measurements. The results show that output parameters such as spatial SPL, average spatial SPL, structure-borne SPL and airborne SPL improve the testing root mean square error to around 20% as compared to randomly assigning the number of neurons for each hidden layer. The testing RMSE in the output parameters has improved when compared with a multi-layer perceptron, sparse autoencoder, Softmax, self-taught learning and extreme learning machine.
Die Bedeutung und Effizienz interdisziplinärer Frühförderung für Kinder mit Beeinträchtigung oder drohender Behinderung – eine Literaturrecherche
Authors: Resch Bernhard , Hasenbacher Vanessa , Kurz Ronald 
Published: July 2020

Zusammenfassung
Hintergrund
Interdisziplinäre Frühförderung (IFF) basiert auf 4 Grundprinzipien: der Ganzheitlichkeit, der Familienorientierung, der Interdisziplinarität und der Vernetzung. Es gibt eine Vielzahl an Methoden und sehr verschiedene Risikogruppen, sodass eine Beurteilung oder eine allgemeingültige Aussage zur Effektivität von IFF schwierig erscheint und Untergruppen je nach Risikogruppe indiziert sind.

Methodik
Wir führten eine Literaturrecherche zum Thema Effizienz der IFF via PubMed, MedLine, Embase und CINAHL durch. Der Suchzeitraum für die verwendete Literatur reichte von 1. Januar 1990 bis zum 30. April 2019. Berücksichtigt wurde Literatur in englischer und deutscher Sprache und Suchbegriffe waren „early childhood intervention“ kombiniert mit „effects, development, disability, prematurity“ etc.

Ergebnisse
Wir analysierten schließlich 50 Publikationen aufgeteilt in 5 Risikogruppen: Frühgeborene, körperliche Behinderung, Autismus-Spektrum-Störung inklusive Sprachentwicklungsverzögerungen, Verhaltensauffälligkeiten und psychosoziale Risiken. In insgesamt 39 der 50 analysierten Publikationen (78 %) einschließlich 4 Reviews bzw. Metaanalysen sowie 2 Cochrane-Reviews ließen sich positive Effekte der IFF nachweisen. Diese wurden in Studien mit kleinen Stichprobengrößen sowie in Publikationen mit großen Probandenzahlen beobachtet.

Zusammenfassung
IFF kann Kindern mit Beeinträchtigungen oder diesbezüglichen Gefährdungen und deren Eltern helfen und vermag, eine Entwicklungsstörung zu verhindern oder abzuschwächen. Aufgrund der Heterogenität der möglichen Interventionsarten und deren Intensitäten ist eine generelle Aussage zur Effizienz trotz der positiven Literaturrecherche schwierig zu treffen, denn es müssen alle Frühfördermaßnahmen individuell an jedes Kind angepasst werden.
[FeFe]-hydrogenase maturation: H-cluster assembly intermediates tracked by electron paramagnetic resonance, infrared, and X-ray absorption spectroscopy
Authors: Németh Brigitta , Senger Moritz , Redman Holly J. , Ceccaldi Pierre , Broderick Joan , Magnuson Ann , Stripp Sven T. , Haumann Michael , Berggren Gustav 
Published: July 2020

Abstract
Abstract
[FeFe]-hydrogenase enzymes employ a unique organometallic cofactor for efficient and reversible hydrogen conversion. This so-called H-cluster consists of a [4Fe–4S] cubane cysteine linked to a diiron complex coordinated by carbon monoxide and cyanide ligands and an azadithiolate ligand (adt = NH(CH2S)2)·[FeFe]-hydrogenase apo-protein binding only the [4Fe–4S] sub-complex can be fully activated in vitro by the addition of a synthetic diiron site precursor complex ([2Fe]adt). Elucidation of the mechanism of cofactor assembly will aid in the design of improved hydrogen processing synthetic catalysts. We combined electron paramagnetic resonance, Fourier-transform infrared, and X-ray absorption spectroscopy to characterize intermediates of H-cluster assembly as initiated by mixing of the apo-protein (HydA1) from the green alga Chlamydomonas reinhardtii with [2Fe]adt. The three methods consistently show rapid formation of a complete H-cluster in the oxidized, CO-inhibited state (Hox-CO) already within seconds after the mixing. Moreover, FTIR spectroscopy support a model in which Hox-CO formation is preceded by a short-lived Hred′-CO-like intermediate. Accumulation of Hox-CO was followed by CO release resulting in the slower conversion to the catalytically active state (Hox) as well as formation of reduced states of the H-cluster.

Graphic abstract
Machine learning for research on climate change adaptation policy integration: an exploratory UK case study
Authors: Biesbroek Robbert , Badloe Shashi , Athanasiadis Ioannis N. 
Published: July 2020

AbstractUnderstanding how climate change adaptation is integrated into existing policy sectors and organizations is critical to ensure timely and effective climate actions across multiple levels and scales. Studying climate change adaptation policy has become increasingly difficult, particularly given the increasing volume of potentially relevant data available, the validity of existing methods handling large volumes of data, and comprehensiveness of assessing processes of integration across all sectors and public sector organizations over time. This article explores the use of machine learning to assist researchers when conducting adaptation policy research using text as data. We briefly introduce machine learning for text analysis, present the steps of training and testing a neural network model to classify policy texts using data from the UK, and demonstrate its usefulness with quantitative and qualitative illustrations. We conclude the article by reflecting on the merits and pitfalls of using machine learning in our case study and in general for researching climate change adaptation policy.
The effect of long-term care public benefits and insurance on informal care from outside the household: empirical evidence from Italy and Spain
Authors: Courbage Christophe , Montoliu-Montes Guillem , Wagner Joël 
Published: July 2020

AbstractThis article uses cross-sectional data from the Survey of Health, Ageing, and Retirement in Europe (SHARE) database to test the effect of both long-term care (LTC) public benefits and insurance on the receipt of informal care provided by family members living outside the household in Italy and Spain. The choice of Italy and Spain comes from the fact that informal care is rather similar in these two countries while their respective public LTC financing systems are different. Our results support the hypothesis of LTC public support decreasing the receipt of informal care for Spain while reject it for Italy. They tend to confirm that the effect of public benefits on informal care depends on the typology of public coverage for LTC whereby access to proportional benefits negatively influences informal care receipt while access to cash benefits exerts a positive effect. Our results also suggest that private LTC insurance complements the public LTC financing system in place.
High aspect ratio cellulose nanofibrils from macroalgae Laminaria hyperborea cellulose extract via a zero-waste low energy process
Authors: Onyianta Amaka J. , O’Rourke Dominic , Sun Dongyang , Popescu Carmen-Mihaela , Dorris Mark 
Published: July 2020

Abstract
Homogeneous high aspect ratio cellulose nanofibrils (CNFs) were prepared from Laminaria hyperborea (LH) seaweed cellulose without any initial mechanical, biological or chemical pre-treatments. Fourier-transform infrared spectrophotometry revealed that LH cellulose was of the cellulose Iα allomorph, typical of algal cellulose. Compared with wood derived CNF, significant enhancements in crystallinity, viscoelastic properties, water retention values (WRV) and morphological characteristics were identified with a single pass at 1 wt. % cellulose content through a high-pressure homogeniser. Further mechanical fibrillation did not lead to appreciable improvements in material properties that would justify the added energy consumption, which at a single pass is at least a factor of 10 lower than with wood cellulose processing. Good quality CNFs with little compromise in material properties were also obtainable at 2–3 wt. % cellulose contents as identified from viscoelastic analysis, WRV and morphological analysis. LHCNFs also showed good thermal stability, which in summary presents a multifunctional high value cellulose nanomaterial that can find application in various fields.

Graphic abstract
Long-term strategies to control COVID-19 in low and middle-income countries: an options overview of community-based, non-pharmacological interventions
Authors: Chowdhury Rajiv , Luhar Shammi , Khan Nusrat , Choudhury Sohel Reza , Matin Imran , Franco Oscar H. 
Published: July 2020

AbstractIn low and middle-income countries (LMICs), strict social distancing measures (e.g., nationwide lockdown) in response to the COVID-19 pandemic are unsustainable in the long-term due to knock-on socioeconomic and psychological effects. However, an optimal epidemiology-focused strategy for ‘safe-reopening’ (i.e., balancing between the economic and health consequences) remain unclear, particularly given the suboptimal disease surveillance and diagnostic infrastructure in these settings. As the lockdown is now being relaxed in many LMICs, in this paper, we have (1) conducted an epidemiology-based “options appraisal” of various available non-pharmacological intervention options that can be employed to safely lift the lockdowns (namely, sustained mitigation, zonal lockdown and rolling lockdown strategies), and (2) propose suitable application, pre-requisites, and inherent limitations for each measure. Among these, a sustained mitigation-only approach (adopted in many high-income countries) may not be feasible in most LMIC settings given the absence of nationwide population surveillance, generalised testing, contact tracing and critical care infrastructure needed to tackle the likely resurgence of infections. By contrast, zonal or local lockdowns may be suitable for some countries where systematic identification of new outbreak clusters in real-time would be feasible. This requires a generalised testing and surveillance structure, and a well-thought out (and executed) zone management plan. Finally, an intermittent, rolling lockdown strategy has recently been suggested by the World Health Organization as a potential strategy to get the epidemic under control in some LMI settings, where generalised mitigation and zonal containment is unfeasible. This strategy, however, needs to be carefully considered for economic costs and necessary supply chain reforms. In conclusion, while we propose three community-based, non-pharmacological options for LMICs, a suitable measure should be context-specific and based on: (1) epidemiological considerations, (2) social and economic costs, (3) existing health systems capabilities and (4) future-proof plans to implement and sustain the strategy.
Scalable design and algorithm for science DMZ by considering the nature of research traffic
Authors: Lee Chankyun , Jang Minseok , Noh Minki , Seok Woojin 
Published: July 2020

AbstractThis paper explores the nature of scientific research traffic on the Korea research environment open network. Based on these investigations, we propose a scalable design and algorithm for the science demilitarization zone (DMZ). The proposed design allows users to share a data-transfer node (DTN), which is essential but costly equipment in the Science DMZ. The proposed iterative greedy algorithm attempts to minimize the peak traffic of the shared DTNs. By considering state-of-the-art DTN and practical research traffic, the proposed design and algorithm achieve up to 79% capital expenditure (CAPEX) reduction from that of a reference design of the Science DMZ where a DTN is allocated per user. The proposed algorithm achieves a 5-order-of-magnitude reduction in computation time at the cost of acceptable CAPEX overheads compared to those of the minimum-CAPEX solutions.
Decentralized master production and recycling scheduling of lithium-ion batteries: a techno-economic optimization model
Authors: Scheller Christian , Schmidt Kerstin , Spengler Thomas Stefan 
Published: July 2020

AbstractDue to the rapid growth of e-mobility, increasing amounts of lithium-ion batteries are produced and returned after their lifetime. However, these returns will lead to new challenges for manufacturers and recyclers, considering the end-of-life. Especially the increasing interaction between forward and reverse supply chain and the related decision on the end-of-life options (e.g., recycling, remanufacturing, and reuse) need to be planned and executed in a sophisticated way. Therefore, we focus on the interactions between recycler and manufacturer as two of the major actors of each supply chain. We formulate optimization models for the master recycling scheduling and the master production scheduling. To analyze current decentralized decisions of the recycler and remanufacturer, we further formulate an integrated master production and recycling scheduling model. In the following, we describe the production and recycling of lithium-ion batteries in a case study. Here, we examine five different scenarios. We find that for all scenarios, manufacturer and recycler achieve positive contribution margins. However, inefficiencies always occur due to opportunistic behavior. As a result, reuse is performed only in case of centralized planning. Hence, coordination is needed between the forward and reverse supply chain to achieve the maximal contribution margin.
Maternal Hypertension, Advanced Doppler Haemodynamics and Therapeutic Precision: Principles and Illustrative Cases
Authors: Phillips Rob A. , Ma Z. , Kong B. , Gao L. 
Published: July 2020

Abstract
Purpose of Review
Maternal hypertension is a common and serious condition associated with increased maternal and foetal morbidity and mortality, with early detection and management improving outcomes.

Recent Findings
Blood pressure (BP) changes of pre-eclampsia are defined after 20 gestational weeks, while haemodynamic changes can be detected at 5–11 weeks using a specialised non-invasive Doppler stroke volume (SV) monitor. Thus, advanced haemodynamic monitoring allows for physiologically precise identification of circulatory abnormalities, and implementation of appropriate therapy within the first trimester. We measured the oscillometric BP and advanced haemodynamics (USCOM 1A) of 3 unselected women with singleton pregnancies, consecutively listed for therapeutic induction for maternal hypertension at 32–41 weeks gestational age. While the BP’s of the patients varied, it was the haemodynamics, particularly SV, cardiac output, systemic vascular resistance, Smith Madigan Inotropy Index, and oxygen deliver, that identified differing patterns of circulatory dysfunction, therapeutic objectives, and predicted post-partum complications of the mother and child.

Summary
First trimester screening of maternal haemodynamics may allow for earlier detection of circulatory derangements, selection of patient precise interventions, and improved maternal-foetal outcomes.
Effect of Gemcitabine based chemotherapy on the immunogenicity of pancreatic tumour cells and T-cells
Authors: Smith P. L. , Yogaratnam Y. , Samad M. , Kasow S. , Dalgleish A. G. 
Published: July 2020

AbstractPurposeChemotherapy for advanced pancreatic cancer has limited efficacy due to the difficultly of treating established tumours and the evolution of tumour resistance. Chemotherapies for pancreatic cancer are typically studied for their cytotoxic properties rather than for their ability to increase the immunogenicity of pancreatic tumour cells. In this study Gemcitabine in combination with immune modulatory chemotherapies Oxaliplatin, zoledronic acid and pomalidomide was studied to determine how combination therapy alters the immunogenicity of pancreatic tumour cell lines and subsequent T-cell responses.MethodsPancreatic tumour cell lines were stimulated with the chemotherapeutic agents and markers of immune recognition were assessed. The effect of chemotherapeutic agents on DC function was measured using uptake of CFSE-stained PANC-1 cells, changes in markers of maturation and their ability to activate CD8+ T-cells. The effect of chemotherapeutic agents on T-cell priming prior to activation using anti-CD3 and anti-CD28 antibodies was determined by measuring IFN-γ expression and Annexin V staining using flow cytometry.ResultsThese agents demonstrate both additive and inhibitory properties on a range of markers of immunogenicity. Gemcitabine was notable for its ability to induce the upregulation of human leukocyte antigen and checkpoints on pancreatic tumour cell lines whilst inhibiting T-cell activation. Pomalidomide demonstrated immune modulatory properties on dendritic cells and T-cells, even in the presence of gemcitabine.DiscussionThese data highlight the complex interactions of different agents in the modulation of tumour immunogenicity and immune cell activation and emphasise the complexity in rationally designing chemo immunogenic combinations for use with immunotherapy.
Controlling human platelet activation with calcium-binding nanoparticles
Authors: Cabrera David , Walker Karen , Moise Sandhya , Telling Neil D. , Harper Alan G. S. 
Published: July 2020

AbstractHuman platelets aggregate at sites of blood vessel damage in response to a rise in their cytosolic calcium concentration. Controlling these cytosolic calcium rises would provide a method to inhibit platelet activation and prevent the unwanted blood clots that causes heart attack and strokes. Previously we have predicted that calcium accumulation within the lumen of an infolded portion of the platelet plasma membrane called the open canalicular system (OCS) is essential for maintaining this cytosolic calcium rise. Due to its nanometer dimensions of the OCS, it has been difficult to measure or interfere with the predicted luminal calcium accumulation. Here we utilise iron oxide magnetic nanoparticles coated with the known calcium chelator, citrate, to create calcium-binding nanoparticles. These were used to assess whether an OCS calcium store plays a role in controlling the dynamics of human platelet activation and aggregation. We demonstrate that citrate-coated nanoparticles are rapidly and selectively uptaken into the OCS of activated human platelets, where they act to buffer the accumulation of calcium there. Treatment with these calcium-binding nanoparticles reduced thrombin-evoked cytosolic calcium rises, and slowed platelet aggregation and clot retraction in human platelets. In contrast, nanoparticles that cannot bind calcium have no effect. This study demonstrates that the OCS acts as a key source of calcium for maintaining cytosolic calcium rises and accelerating platelet aggregation, and that calcium-binding nanoparticles targeted to the OCS could provide an anti-platelet therapy to treat patients at risk of suffering heart attacks or strokes.