bluuebunny/crossref_metadata_2025_split huggingface dataset:
Untersuchung des Dickdarm-Mikrobioms in der klinischen Forschung
Authors: Hiergeist Andreas , Manook André , Gessner André , Rupprecht Rainer , Baghai Thomas C. 
Published: February 2020

ZUSAMMENFASSUNG
Gegenstand und Ziel: Analysen des Dickdarm-Mikrobioms sind ein international zunehmend intensiver untersuchter Forschungsschwerpunkt. Die zahlreichen Schwierigkeiten solcher Studien sind oft nicht bekannt, worauf hier vermehrt aufmerksam gemacht werden soll. Antidepressiva und Antibiotika zeigen teils ähnliche Wirkmechanismen, weshalb erneut psychiatrische Indikationen für Antibiotika geprüft werden. Vor diesem Hintergrund zeigen wir Daten einer Feldbeobachtung an der Universität Regensburg.
Material und Methoden: 179 Teilnehmer spendeten eine Stuhlprobe und füllten das Regensburg Microbiome Questionnaire (ReMBiQ) aus. Das bakterielle Mikrobiom aller Stuhlproben wurde mittels 16S-rRNA-Hochdurchsatz-Sequenzierung analysiert. Anhand des ReMBiQ wurde eine Subkohorte ausgewählt: Zu einer Teilnehmerin mit seit 18 Monaten behandelter MDR-Tuberkulose wurden 4 gesunde Kontrollen anhand zahlreicher und für das Dickdarm-Mikrobiom relevanter Kriterien ausgewählt.
Ergebnisse: Mikrobiomtypische Parameter wie Alpha- und Beta-Diversität grenzten die Teilnehmerinnen innerhalb der Subkohorte klar voneinander ab. Hierbei half auch die Messung absoluter Bakterienmengen mittels spike-in-based calibration to total microbial load (SCML). Insgesamt fiel im Vergleich insbesondere eine deutliche Zunahme der Gattung Bacteroides auf, die mit 94,5 % dominierte.
Schlussfolgerungen: Unterschiedliche Ergebnisse bei gleichen oder ähnlichen, starken Eingriffen im Dickdarm, verdeutlichen die Notwendigkeit strenger methodischer Standards. Dies gilt insbesondere für die Beobachtung vergleichsweise kleiner Effektgrößen in den Neurowissenschaften.
Klinische Relevanz: Die neurowissenschaftliche Bewertung des Dickdarm-Mikrobioms unter kombiniert antidepressiv-antimikrobieller Therapie wird wichtige Hinweise auf die Wirksamkeit neuer Therapieformen liefern.
Workload Intensity and Rest Periods in Professional Ballet:
Connotations for Injury
Authors: Kozai Andrea C. , Twitchett Emily , Morgan Sian , Wyon Matthew Alexander 
Published: February 2020

AbstractFatigue and overwork have been cited as the main cause of injury with the dance
profession. Previous research has shown a difference in workload between
professional dancers of different rank, but the role of sex has not been
examined. The purpose of this study was to determine workload intensity, rest,
and sleep profiles of professional ballet dancers. 48 professional ballet
dancers (M=25, F=23) took part in an observational design over
7–14 days using triaxial accelerometer devices. Minutes in METS at
different intensities, total time asleep and rest breaks were analysed.
Significant main effects for rank (p<0.001) and rank by sex
(p=0.003) for total PA, working day activity, post work activity and
sleep. Sleep ranged between 2.4–9.6 h per night. All
participants spent more time between 1.5–3 METS outside of work.
Significant amounts of exercise where carried out outside of their work day,
therefore when injury is reported per 1000 h dance activity, this
extra-curricular activity might need to be included. When looking at potential
causes of injury in dance, a global perspective of physical activity is required
that includes activity outside of work and sleep patterns, all activities that
influence physiological recovery.
Updates on the Management of Thyroid Cancer
Authors: Araque Katherine A. , Gubbi Sriram , Klubo-Gwiezdzinska Joanna 
Published: February 2020

AbstractThe diagnostic modalities, stratification tools, and treatment options for
patients with thyroid cancer have rapidly evolved since the development of
the American Thyroid Association (ATA) guidelines in 2015. This review
compiles newer concepts in diagnosis, stratification tools and treatment
options for patients with differentiated thyroid cancer (DTC), medullary
thyroid carcinoma (MTC) and anaplastic thyroid cancer (ATC). Newer
developments apply precision medicine in thyroid cancer patients to avoid
over-treatment in low risk disease and under-treatment in high risk disease.
Among novel patient-tailored therapies are selective RET inhibitors that
have shown efficacy in the treatment of MTC with limited systemic toxicity
compared with non-specific tyrosine kinase inhibitors. The combination of
BRAF and MEK inhibitors have revolutionized management of BRAF V600E
mutant ATC. Several immunotherapeutic agents are being actively investigated
in the treatment of all forms of thyroid cancer. In this review, we describe
the recent advances in the diagnosis and management of DTC, MTC, and ATC,
with an emphasis on novel treatment modalities.
The Influence of Thyroid Hormones on Brain Structure and Function in
Humans
Authors: Göbel Anna , Göttlich Martin , Reinwald Jonathan , Rogge Berenike , Uter Jan-Christoph , Heldmann Marcus , Sartorius Alexander , Brabant Georg , Münte Thomas F. 
Published: February 2020

AbstractThe pleiotropic function of thyroid hormones (TH) is mediated by an organ
specific expression of thyroid hormone transporters, deiodinases and TH
receptors. In a series of studies we used the model of an experimentally induced
hyper- or hypothyroidism in human volunteers to delineate TH action on the
brain. A battery of neuropsychological testing paradigms was employed and
complemented by structural and functional multimodal neuroimaging.
Experimentally induced mild thyrotoxicosis for 6 weeks was associated with
changes in brain structure (determined with voxel-based morphometry), resting
state functional connectivity, and task-related functional activation in a
working memory paradigm. Partial withdrawal of TH replacement in patients
without thyroid (subclinical hypothyroidism) likewise lead to changes on
multiple functional and structural brain measures. Importantly, the series of
studies reviewed here identified the cerebellum as one crucial site of
action.
Current Trends in Operative Treatment of Scaphotrapeziotrapezoid Osteoarthritis: A Survey among European Hand Surgeons
Authors: Berkhout Merel J.-L. , Yin Qiqi , Ritt Marco J. P. F. 
Published: February 2020

Abstract
Objective Based on the available evidence, the optimal surgical treatment for isolated scaphotrapeziotrapezoid oarthritis (STT OA) remains unclear. The purpose of this study is to explore the prevailing surgical practice for isolated STT OA among European hand surgeons. We hypothesized that a considerable variance exists in the current surgical practice among hand surgeons in Europe.
Methods An online survey was distributed to 20 participating member states of the Federation of European Societies for Surgery of the Hand (FESSH). Respondents were questioned on their country of practice, surgical experience, preferred surgical procedure, frequency of performing this procedure, factors in decision-making, and other performed surgical procedures.
Results Four hundred and sixty-five responses were received with an estimated response rate of 19%. Trapeziectomy with partial trapezoidal excision was the surgical treatment of choice among the participating hand surgeons in Europe (38%), followed by STT joint fusion (30%), and distal scaphoid excision (14%).
Conclusion This survey provides an insight into the surgical management of isolated STT OA among hand surgeons in Europe. A wide variety of preferred treatment techniques were found. Evidence concerning the optimal surgical treatment has not been established. Future prospective randomized studies comparing different techniques are warranted.
Harnessing transition waves to realize deployable structures
Authors: Zareei Ahmad , Deng Bolei , Bertoldi Katia 
Published: February 2020

Significance
From foldable chairs and umbrellas to tents and solar panels, many structures are capable of quickly changing their shape and therefore, function. The design of these deployable structures poses two main challenges. First, transformation needs to be reliable and autonomous, and second, systems have to be stable and locked in place in the deployed state. Using a combination of experiments and analyses, we demonstrate that bistable linkages and transition waves provide a powerful platform for realizing deployable structures. We first carefully design the bistable joints so that the transition wave propagates through the entire linkage, transforming the initial straight structure into a curved one. Then, we use these elements as building blocks to create deployable three-dimensional structures of arbitrary shape.
Aiming for advanced intelligibility and proficiency using mobile ASR
Authors: Mroz Aurore 
Published: February 2020

Abstract
This experimental study aimed to determine the impact of mobile-based Automatic Speech Recognition (ASR) in Gmail
on intelligibility and proficiency, as well as whether any individual factors influenced learning outcomes. It focused on 26
Intermediate learners of French as a foreign language enrolled in two university courses geared towards the development of
advanced oral skills but with different approaches to integrated instruction. It innovatively combined human-based and
machine-based ratings within an ecological paradigm, following Levis’s (2005)
intelligibility principle and Thomson and Derwing’s (2015) call for research that is
readily useful for language instructors. Results show that ASR users significantly outperformed non-ASR users on intelligibility,
particularly when exposed to instruction on spelling-to-sound patterns, and demonstrated the biggest growth in proficiency. Gender
was also found to impact results. Pedagogical implications and venues for future research are offered.
Current interruption performance of ultrahigh-pressure nitrogen arc
Authors: Abid Fahim , Niayesh Kaveh , Espedal Camilla , Støa-Aanensen Nina 
Published: February 2020

Abstract
In this paper, the influence of gas filling pressure on the current interruption performance of different switch configurations with electric arcs burning in nitrogen has been experimentally investigated. A synthetic circuit generating a current of 130 A at 190 Hz is used and the initial rate of rise of recovery voltage just after current zero is varied from 9.8 V/µs to 84.9 V/µs. To evaluate the effect of forced gas flow on current interruption performance, three different test arrangements are investigated: a simple contact configuration with a free-burning arc, a contact and a cylindrical nozzle setup (tube-constricted arc), and finally a self-blast arrangement where the arc is cooled by a gas flow near current zero. In each arrangement, three different filling pressures are mainly studied: 1, 20, and 40 bar, the latter being in the supercritical region. In all cases, the interelectrode gap is fixed at 50 mm. It is observed that the interruption performance deteriorates with increased filling pressure in the absence of forced gas flow. A higher post-arc current is observed for the arcs burning at high filling pressures (i.e. 20 and 40 bar) compared to at atmospheric pressure in cases with no or little forced cooling. On the other hand, a forced gas flow near the current zero reduces the post-arc current and improves the interruption performance also at high filling pressures. Little effect of the supercritical state on the interruption performance of nitrogen is observed. Under the above-mentioned test conditions, the majority of the failures at high filling pressure are observed to be of thermal re-ignition type.
Mechanical characteristic of laminated beam of teak wood with sengonusing connector
Authors: Galuh D L C , Sulistyorini D , Sutadi D 
Published: February 2020

Abstract
Wood as construction material which is provided by nature is decreasing if the usage is not controlled. Several kinds of wood which are often used for construction material are teak wood and sengon wood. One alternative combines wood with good quality and deficient quality, such as combination of teak wood and sengon wood as laminated beam. This research is to know flexural load of perpendicular layered connection of teak wood and sengon wood with bolt and nail connector. The teak wood was placed at the bottom and the sengon wood was at the top. Dimension of wood beam test specimen before laminated was 60 x 100 x 800 mm, after being laminated was 120 x 100 x 800 mm with 2 variations of connector of bolts and nails. Each connector was made in 3 test specimens. The bolt diameter size was 7 mm, the nail size was 5 mm, the length was 150 mm and the range of each connector was160 mm. Installation of connector was carried out parallel for each specimen test, so that there were 4 connectors in each laminated beam. The flexural load of laminated beam test specimen of teak wood with sengon wood using nail connector is bigger 19.2 % than laminated beam using bolt connector although the diameter is smaller. The use of laminated beam with nail connector becomes alternative substitute of whole beam.
EEG dataset classification using CNN method
Authors: Mao W-L , Fathurrahman H I K , Lee Y , Chang T W 
Published: February 2020

Abstract
This paper proposes a simple Convolutional Neural Network (CNN) program to classify epileptic seizure. The diagnosis of epileptic seizure involves the identification and different characteristic of the Electroencephalography (EEG) signal. As such, it needs a method for identifying and classifying epileptic seizure. Deep learning is part of a neural network that has the ability and pattern to identify and classify epileptic seizure. CNN has been demonstrated high performance on image classification and pattern detection. In this paper, we combine the continuous wavelet transform (CWT) and CNN to classify epileptic seizure. This experiment uses the wavelet transform to convert signal data of EEG to time-frequency domain images. The output of the wavelet transform is an image that will classify into five attributes. In this experiment, we develop a simple program that will compare with other CNN approach (AlexNet and GoogleNet). The results of this experiment are two kinds of data, accuracy, and loss. The resulting accuracy is 72.49%, and the loss is 0.576. This result has a better learning time than GoogleNet and smaller loss result than AlexNet.
Factors affecting the use of mobile news applications
Authors: Pambudi S , Maarif F , Gao Z 
Published: February 2020

Abstract
The objective of this study was to analyze the factors that influence the use of mobile news applications. The research model used in this study was adapted from the Unified Theory of Acceptance and Use of Technology (UTAUT). This study was classified as a quantitative study with data processing using Structural Equation Modeling (SEM). The results of this study indicated that the Perceived Visual Attractiveness, Perceived Enjoyment, Performance Expectancy, and Effort Expectancy had a positive effect, but Image has no positive effect on Behavioral Intention in using mobile news applications. Also, perceived Behavioral Control and Behavioral Intention have a positive effect on Use Behavior.
Consumer price index prediction using Long Short Term Memory (LSTM) based cloud computing
Authors: Zahara S , Sugianto  , Ilmiddaviq M B 
Published: February 2020

Abstract
Long Short Term Memory (LSTM) is known as optimized Recurrent Neural Network (RNN) architectures that overcome the lack of RNN’s about maintaining long period of memories information. As part of machine learning networks, LSTM also notable as the right choice for time-series prediction. Inflation rate has been used for decision making for central banks also private sector. In Indonesia, CPI (Consumer Price Index) is one of best practice inflation indicators besides Wholesale Price Index and The Gross Domestic Product (GDP). Since CPI data could be used as a direction for next inflation move, we conducted CPI prediction model using Long Short Term Memory Method. The network model input consists of 34 variables of staple price in Surabaya and the output is CPI value. In the interest of predictive accuracy improvement, we used several optimization algorithm i.e. Stochastic Gradient Descent (sgd), Root Mean Square Propagation (RMSProp), Adaptive Gradient (AdaGrad), Adaptive moment (Adam), Adadelta, Nesterov Adam (Nadam) and Adamax. The result indicate that Nesterov Adam has 4.088 RMSE’s value, less than other algorithm which indicate the most accurate optimization algorithm to predict CPI value.
Numerical simulation of fluid flow characteristics at oxygen gas tank with variations compressibility values using openfoam
Authors: Syamsuri  , Maulana H S , Setyono G 
Published: February 2020

Abstract
Oxygen gas tank is one application of the decompression tank, which is filled with oxygen with a certain pressure. Oxygen storage tubes is very vital in the health sector, both at the clinic and at the hospital, because most people who are sick or who will undergo surgery in desperate need of clean oxygen. In this study the decompression tank was analyzed using numerical simulation methods using OpenFOAM software. Three different compressibility values of oxygen gas (6.90e-03, 6.90e-04, and 6.90e-05) varied in this study. This is done to find out the results of the pressure distribution and velocity in the tank. From the results of the study with variations in oxygen gas compressibility values, we can know that each compressibility value has different pressure distribution and velocity characteristics even though with the same time and the smaller the compressibility value, the pressure distribution and velocity produced are wider and faster propagating
A possibility of artificial neural networks to be applied in the predictive test: A systematic literature review and study case
Authors: Asmara A 
Published: February 2020

Abstract
Artificial Neural Network (ANN’s) was developed continuously and applied to each smart technology. The developing smart tests are continuous with ANN’s possibility applied to increase efficiencies and time of decides. The Predictive Test was developed using the Smart Algorithm with the possibility of ANN to apply. Assessments of ANN implementation have been carried out based on a study in past time. The systematic literature review was used to found possibility implementation ANN’s in the predictive test and combined with the study case. The result showed as ANN’s could implement in the predictive test that used big data inputs. In addition, ANN’s can be implantation on the predictive test such as education predictive test, talent and aptitude test or psychological test.
Digitizing learning assessment to develop students’ critical thinking
Authors: Yulia Y , Susilowati I 
Published: February 2020

Abstract
The objective of this paper is to design a learning assessment program in this education revolution 4.0, the so-called Plickers. It is one of the innovative on-line applications for students’ reading assessment triggering students’ critical thinking as well as their creativity. This research belongs to Educational Research and Development (R&D) which is divided into three main stages: exploration, development, and field-testing phase. The data analysis of this research used descriptive qualitative. Some interviews, document analysis, and classroom observation were employed to collect the data of this study. The reading test through Plickers was designed based on students’ need. The finding shows that both teachers and students positively responded to digitize their learning assessment to accomodate both their critical thinking and creativity.
Increased risk of malaria transmission with warming temperature in the Ethiopian Highlands
Authors: Endo Noriko , Eltahir Elfatih A B 
Published: February 2020

Abstract
The heavily populated highlands of Ethiopia are currently at low risk for malaria transmission, but global warming may change the risk level significantly. The inhabitants of the Ethiopian Highlands are highly vulnerable to this potential hazard due to their lack of immunity. Here, we identify hotspots within the Highlands where projected warming towards the end of the 21st century will increase the risk of malaria transmission significantly. Based on projected temperature changes, we conclude that about a third of the region’s population and roughly 14% of its land area will become at high risk for malaria transmission within a century under the high-emissions-no-mitigation baseline scenario for future climate change. Our analysis combines dynamically down-scaled regional climate projections, high resolution satellite observations of temperature, and a village-scale malaria transmission model that was developed based on climatic, environmental, entomological, and medical data collected by our group in comprehensive multi-year field surveys of villages in this region. The projected impacts of global warming on malaria transmission in Africa have been controversial. We propose a framework that reconciles seemingly contradictory conclusions, and informs strategies for climate adaptation not only over the Ethiopian Highlands but broadly over Africa, where more than 90% of malaria deaths occur every year.
Analysing the Influence of Cognitive, Affective, Conative, and Motivation Aspects on Train Passenger’s Deviant Behaviour: Commuter Line, Indonesia
Authors: Zubair A , Chotib  
Published: February 2020

Abstract
Commuter Line in Jakarta and surrounding cities became the best public transportation for urban choice. However, there are still many problems related to behavior deviations. There are several forms of deviant behavior found, such as pickpocketing, sexual abuse, smoking, aggressive passengers, eating and drinking in the carriage, and priority seat abuse. The purpose of this paper is to analyze whether there is a significant influence among the cognitive, affective, conative, and motivation aspects of passengers simultaneously and partially to deviant behavior. Mixed-Method research is conducted to understand behavior aspects. Sequential exploratory research model is used with the main focus to explore a phenomenon of train passenger deviant behavior and divided into two stages. The first stage is the collection of qualitative data using observation and in-depth interview methods. The second stage is collecting quantitative data with the survey and distributing questionnaires methods. Multiple linear regression and triangulation analysis are used in this study with several tests such as hypothesis test and coefficient of determination test. The results showed some implication about passenger deviant behavior based on four aspects: cognitive, affective, conative, and motivation. The conclusions explained cognitive, motivation and, conative aspects show very strong influence on deviant behavior.