bluuebunny/crossref_metadata_2025_split huggingface dataset:
Multi-atlas label fusion with random local binary pattern features: Application to hippocampus segmentation
Authors: Zhu Hancan , Tang Zhenyu , Cheng Hewei , Wu Yihong , Fan Yong 
Published: November 2019

AbstractAutomatic and reliable segmentation of the hippocampus from magnetic resonance (MR) brain images is extremely important in a variety of neuroimage studies. To improve the hippocampus segmentation performance, a local binary pattern based feature extraction method is developed for machine learning based multi-atlas hippocampus segmentation. Under the framework of multi-atlas image segmentation (MAIS), a set of selected atlases are registered to images to be segmented using a non-linear image registration algorithm. The registered atlases are then used as training data to build linear regression models for segmenting the images based on the image features, referred to as random local binary pattern (RLBP), extracted using a novel image feature extraction method. The RLBP based MAIS algorithm has been validated for segmenting hippocampus based on a data set of 135 T1 MR images which are from the Alzheimer’s Disease Neuroimaging Initiative database (adni.loni.usc.edu). By using manual segmentation labels produced by experienced tracers as the standard of truth, six segmentation evaluation metrics were used to evaluate the image segmentation results by comparing automatic segmentation results with the manual segmentation labels. We further computed Cohen’s d effect size to investigate the sensitivity of each segmenting method in detecting volumetric differences of the hippocampus between different groups of subjects. The evaluation results showed that our method was competitive to state-of-the-art label fusion methods in terms of accuracy. Hippocampal volumetric analysis showed that the proposed RLBP method performed well in detecting the volumetric differences of the hippocampus between groups of Alzheimer’s disease patients, mild cognitive impairment subjects, and normal controls. These results have demonstrated that the RLBP based multi-atlas image segmentation method could facilitate efficient and accurate extraction of the hippocampus and may help predict Alzheimer’s disease. The codes of the proposed method is available (https://www.nitrc.org/frs/?group_id=1242).
A novel therapeutic approach using peripheral blood mononuclear cells preconditioned by oxygen-glucose deprivation
Authors: Hatakeyama Masahiro , Kanazawa Masato , Ninomiya Itaru , Omae Kaoru , Kimura Yasuko , Takahashi Tetsuya , Onodera Osamu , Fukushima Masanori , Shimohata Takayoshi 
Published: November 2019

AbstractCell therapies that invoke pleiotropic mechanisms may facilitate functional recovery in patients with stroke. Based on previous experiments using microglia preconditioned by oxygen-glucose deprivation, we hypothesized that the administration of peripheral blood mononuclear cells (PBMCs) preconditioned by oxygen-glucose deprivation (OGD-PBMCs) to be a therapeutic strategy for ischemic stroke. Here, OGD-PBMCs were identified to secrete remodelling factors, including the vascular endothelial growth factor and transforming growth factor-βin vitro, while intra-arterial administration of OGD-PBMCs at 7 days after focal cerebral ischemia prompted expression of such factors in the brain parenchyma at 28 days following focal cerebral ischemiain vivo. Furthermore, administration of OGD-PBMCs induced an increasing number of stage-specific embryonic antigen-3-positive cells bothin vitroandin vivo. Finally, it was found to prompt angiogenesis and axonal outgrowth, and functional recovery after cerebral ischemia. In conclusion, the administration of OGD-PBMCs might be a novel therapeutic strategy against ischemic stroke.
Methanol extract of Iphiona aucheri ameliorates CCl4 induced hepatic injuries by regulation of genes in rats
Authors: Zai Jawaid Ahmed , Khan Muhammad Rashid , Mughal Zaib un Nisa , Batool Riffat , Naz Irum , Maryam Sonia , Zahra Zartash 
Published: November 2019

AbstractWe have investigated the protective potential of methanol extract of Iphiona aucheri (IAM) on the expression of endoplasmic reticulum (ER) stress associated genes and inflammatory genes on carbon tetrachloride (CCl4) induced hepatic toxicity in rats. Hepatic damage markers: aspartate aminotransferase (AST), alanine aminotransferase (ALT), alkaline phosphatase (ALP) and bilirubin were elevated while the content of antioxidants: catalase (CAT), superoxide dismutase (SOD), peroxidase (POD) and reduced glutathione (GSH) were decreased significantly (p &lt; 0.05) in CCl4 treated rats as compared to the control group. The CCl4 intoxication induced a higher expression of glucose-regulated protein 78 kDa (GRP78), X-box-binding protein 1 total (XBP1t), spliced X-box-binding protein 1 (XBP1s), unspliced X-box-binding protein 1 (XBP1u), C/EBP homologous protein (CHOP) and genes involved in inflammation and fibrosis: tumor necrosis factor alpha (TNF-α), transforming growth factor-beta (TGF-β), mothers against DPP homolog 3 (SMAD3), alpha skeletal muscle actin (αSMA) and collagen type I alpha 1 chain (COL1A1). The intoxicated rats showed a low expression of the glutamate–cysteine ligase catalytic subunit (GCLC), protein disulfide isomerase (PDI) and nuclear factor (erythroid-derived 2) like-2 (Nrf2). The administration of IAM to intoxicated rats restored the expression of ER stress, inflammatory, fibrosis and antioxidant genes in a dose dependent manner. Our results indicated that IAM can impede the ER stress and inflammatory genes and it could be a complementary and alternative therapeutic agent for oxidative stress associated disorders.
Decision making on the state of transformers based on insulation condition using AHP and TOPSIS methods
Authors: Madavan Rengaraj , Saroja Subbaraj 
Published: November 2019

The evaluation and selection of state of transformers based on their mineral oil data are quite difficult. In this study, analytical hierarchy process (AHP) and technique for order preference by similarity to ideal solutions (TOPSISs) are used as the multi‐criteria decision support methodologies to provide a simple approach to rank transformers based on their mineral oil data and to help decision makers to identify the transformer, which is in the most critical state. AHP is exercised for both priority weight calculation and ranking of transformers. The AHP method is used for weight calculation, and then transformers are ranked using TOPSIS. Here, data of 69 in‐service and 12 failed transformers in Tamil Nadu state in India is collected for assessment. From the results, transformers with good insulation condition are ranked at top, while the transformers are given lower ranks if they are found to have bad health. It is proved that decisions yielded by both methods are in agreement with reality.
Identification of internal fault against external abnormalities in power transformer using hierarchical ensemble extreme learning machine technique
Authors: Raichura Maulik B. , Chothani Nilesh G. , Patel Dharmesh D. 
Published: November 2019

Various unwanted phenomena that are taken place in the transformer may occasionally mal‐operate selected fault classification based protective schemes. Hence, it is necessary to discriminate internal fault from external abnormal conditions for unit protection of power transformer. This study presents a new hierarchical ensemble extreme learning machine (HE‐ELM) based classifier technique to identify faults in & out of transformer. The component extreme learning machine (ELM) is structured hierarchically to improve its fault data classification accuracy. The developed algorithm is evaluated by simulating multiple disorders on 100 MVA, 132/220 kV transformer with the help of PSCAD software. DWT is used to extract features from acquired current signals from transformer. The feature vector formed after extraction process is fed to the HE‐ELM algorithm for data classification. The fault discrimination accuracy of HE‐ELM technique is 99.91%. This shows its effectiveness with respect to other classifier techniques. Moreover, the developed algorithm is successfully tested on hardware prototype in laboratory environment under various inrush and fault conditions using Cortex M4 microcontroller (STM32F407) with maximum identification time of 27 ms. The proposed HE‐ELM technique is compared with existing support vector machine, probabilistic neural network and ELM techniques for identical fault data. Results demonstrate that HE‐ELM outperforms than existing schemes in cross‐domain recognition task.
Prävention im Hautschutzzentrum – ein Konzept zur erfolgreichen Vermeidung von Berufsunfähigkeit
Authors: Siekmann A. , Friedlein H. , Neuber H. 
Published: November 2019

ZusammenfassungBerufsbedingte Erkrankungen der Haut erfordern umfangreiche Maßnahmen zur Verhinderung einer krankheitsbedingten Berufsaufgabe. Adäquate Diagnostik und Therapie sind wichtig, aber zur Wiederherstellung von Arbeitsfähigkeit und hautgesunder Weiterbeschäftigung allein oft nicht ausreichend. Das Konzept eines Hautschutzzentrums vereint alle wesentlichen Voraussetzungen für eine erfolgreiche Intervention in Zusammenarbeit mit den Gesetzlichen Unfallversicherern. Entscheidend ist die zeitnahe, umfassende Evaluation aller Ursachen sowie deren Beseitigung. Je länger die entscheidenden Stellschrauben nicht gedreht werden, desto eher ist durch Chronifizierung und Entstehen von Allergien ein Krankheitszustand erreicht, der ein hautgesundes Weiterarbeiten in dem häufig geliebten Beruf unmöglich macht. Neben organisatorischen und technischen Veränderungen beruht ein wesentlicher Teil des Erfolgs eines Hautschutzzentrums auf der Induktion und dem dauerhaften Etablieren grundlegender Verhaltensänderungen der Betroffenen.
Osteoporose beim Idiopathischem Parkinson-Syndrom: Risikopatienten erkennen, diagnostizieren und richtig behandeln
Authors: Bergmann Philipp , Emmert Kirsten , Maetzler Walter 
Published: November 2019

ZusammenfassungPatienten mit idiopathischem Parkinson-Syndrom (IPS) erkranken deutlich häufiger als die Allgemeinheit an Osteoporose. Dies kann sowohl auf Gemeinsamkeiten in der Pathogenese als auch auf die Begleiterkrankungen des IPS, von denen zahlreiche Risikofaktoren für Osteoporose darstellen, zurückgeführt werden. In diesem Artikel werden verschiedene Risikofaktoren vorgestellt, auf die in der Praxis geachtet werden sollte. Insbesondere wird auf Vitamin D-Mangel, Hyperhomocysteinämie in Zusammenhang mit Levodopa-Einnahme und Mangelernährung sowie Konsequenzen der Immobilität eingegangen. Aufgrund des erhöhten Osteoporoserisikos ist es sinnvoll, dass nach der Diagnosestellung des IPS eine Basisdiagnostik der Osteoporose erfolgt und die IPS-Patienten auch im Verlauf immer wieder auf Osteoporose untersucht werden. Obwohl der Zusammenhang von IPS und Osteoporose allgemein bekannt ist, führt die Diagnose einer Osteoporose beim IPS häufig nicht zu einer ausreichenden Therapie. Konkret kann die Osteoporose bei IPS-Patienten durch Physio- und Ergotherapie, eine Anpassung von Lebensstil (Reduzierung von Alkohol und Nikotinkonsum) und Ernährung, großzügige Supplementierung von Vitamin D und durch Gabe einer spezifischen antiosteoporotischen Medikation, wie z. B. Bisphosphonaten, behandelt werden. Eine Studie, die noch validiert werden muss, zeigt auch einen positiven Effekt einer Substitution von Folsäure und Cobalamin, um die Homocystein-Serumkonzentration zu senken. Bei der medikamentösen Behandlung ist bei IPS-Patienten auch insbesondere zu beachten, dass die orale Einnahme der Medikamente einen suffizienten Schluckakt voraussetzt. Für IPS-Patienten mit kritischer Dysphagie stehen auch parenterale Applikationsformen zur Verfügung. Aufgrund der Komplexität der Behandlung des IPS und der Osteoporose bedarf es somit eines interdisziplinären und multiprofessionellen Behandlungsteams, das Neurologen, Geriater und Ernährungsmediziner mit einschließt.
Depression, Osteoporose, Stürze und Frakturen
Authors: Rapp Kilian , Pfeiffer Klaus 
Published: November 2019

ZusammenfassungDie Depression geht mit einem erhöhten Frakturrisiko einher. Da Fragilitätsfrakturen meist Folge eines Sturzes und/oder einer erhöhten Knochenbrüchigkeit sind, beschreibt die Übersichtsarbeit, über welche Wege die Depression Sturzrisiko und Knochendichte beeinflussen kann.Patienten mit Depression haben ein um 50 % erhöhtes Sturzrisiko. Diskutierte Gründe sind körperliche Inaktivität, Verlust der Muskelmasse und mit einer Depression einhergehende und mit Stürzen assoziierte Gangstörungen. Zudem erhöhen Antidepressiva das Sturzrisiko um ca. 70 %.Bei Patienten mit Depression findet sich auch eine verminderte Knochendichte. Faktoren wie körperliche Inaktivität, geringe Sonnenlichtexposition, Rauchen, Alkoholkonsum und Untergewicht, von denen bekannt ist, dass sie einen negativen Einfluss auf die Knochendichte haben, sind bei depressiven Personen häufiger anzutreffen. Zudem haben die bei Depression beobachtete erhöhte sympathische Aktivität, pro-inflammatorische Zytokine und erhöhte Serumkortisonwerte einen potentiell schädigenden Effekt auf den Knochen. Ein direkt schädigender Effekt auf den Knochen wird für die Substanzklasse der SSRIs diskutiert.Die Beziehung zwischen Depression und Fraktur ist nicht unidirektional. Stürze und Frakturen können ihrerseits zu Sturzangst und Depression führen.Therapeutisch hat körperliches Training einen moderaten Effekt auf die depressive Symptomatik. Für spezifische Sturzpräventionsprogramme konnte dies bisher nicht nachgewiesen werden. Kognitiv-behaviorale Ansätze stehen zur Therapie der Sturzangst zur Verfügung. Der Einsatz von Antidepressiva sollte auf mittelschwere und schwere Depressionen beschränkt werden. Der Beginn sollte mit niedrigen Dosen erfolgen, Blutdruck und Elektrolyte müssen kontrolliert werden. Trizyklische Antidepressiva sollten bei älteren Patienten ganz vermieden werden.Depression/Antidepressiva finden als Risikofaktoren in den DVO-Leitlinien Berücksichtigung.
Phytotherapeutische Antworten auf bakterielle Resistenzentwicklung
Authors: Brendieck-Worm Cäcilia 
Published: November 2019

ZusammenfassungDie Anwendung von sekundären Pflanzenstoffen in Form von, auf Wirksamkeit und Unbedenklichkeit geprüften, Phytopharmaka, wie dem in der Tiermedizin seit langem bewährten Angocin® Anti-Infekt N in Therapiekonzepten gegen Infektionen, ist aus erfahrungsmedizinischer Sicht sinnvoll und medizinisch zu rechtfertigen.Die Therapieerfolge mit Angocin® Anti-Infekt N beim Hund, insbesondere bei Infektionen der Atemwege und der Harnwege, sind überzeugend, insbesondere angesichts des geringen Risikos von unerwünschten Nebenwirkungen.
Organophosphorus-induced extrapyramidal intermediate syndrome in an adolescent suicide attempt survivor
Authors: Sarkar Sumantra , Nandi Madhumita , Mondal Rakesh , Mandal Sandip Kumar 
Published: November 2019

ABSTRACTThe victims of organophosphorus (OP) pesticide poisoning usually present with acute cholinergic crisis, due to the inhibition of the enzyme acetylcholinesterase. Any neurological complication in the form of intermediate syndrome is rare and its presentation with extrapyramidal symptoms is even rarer. The authors report such a case in a 12-year-old adolescent girl, who survived a near lethal suicidal attempt.
A patient with pycnodysostosis presenting with seizures and porencephalic cysts
Authors: Kumar Subhash 
Published: November 2019

ABSTRACTPycnodysostosis is a rare autosomal recessive disorder caused by mutations in the cysteine protease Cathepsin K gene located on chromosome 1q21. It has a well characterized skeletal phenotype which include short stature, generalized increased bone density with propensity of fractures, open calvarial sutures and fontanelle, dental abnormalities, obtuse mandibular angle, resorption of lateral end of clavicle, acro-osteolysis, and in some cases visceromegaly. Central nervous system involvement is very rare and porencephalic cysts has been reported only once, the cause being hypothesised to be an imbalance between the growing brain, its vascular supply and intraventricular fluid pressure. We had a patient with bilateral frontal lobe porencephalic cysts; the patient presenting with complex partial seizures. Cathepsins have been found to be involved in neurological diseases and role of proteases has been well established in gliosis.
Deliberate practice in training differentiates the best Kenyan and Spanish long‐distance runners
Authors: Casado Arturo , Hanley Brian , Ruiz‐Pérez Luis Miguel 
Published: November 2019

AbstractThe aim of this novel research was to compare the amount of systematic training and the different training activities undertaken by elite‐standard long‐distance runners during their first seven years of systematic training. Participants were divided into three performance groups: world‐class Kenyans (N = 19), European‐standard Spanish athletes (N = 18), and Spanish national‐standard athletes (N = 18). Performance and training data were obtained for two‐year periods using retrospective recall (including training diaries) from the time the athletes began systematic training, until the seventh year after. These activities included high‐intensity training sessions considered deliberate practice (DP) and easy runs. There was no evidence that starting systematic training at a younger age was advantageous, and easy runs (a non‐DP activity) were the most used by participants as a proportion of overall running distance. As part of an overall higher accumulation of distance run (P < 0.001, d ≥ 1.35), the Kenyans completed more tempo runs and short‐interval training than the other groups (P < 0.001, d ≥ 1.38), but did not complete more long intervals or races. There were few differences between the European‐ and national‐standard athletes except for easy runs, which highlights the value of these easy runs but also the need for higher‐intensity training to compete with world‐class performers. When planning for training overload and progression, long‐distance running coaches should consider increasing the volume of tempo runs and short intervals, in addition to easier runs that develop cardiovascular conditioning.
Data augmentation for self-paced motor imagery classification with C-LSTM
Authors: Freer Daniel , Yang Guang-Zhong 
Published: November 2019

Abstract

Objective. Brain–computer interfaces (BCI) are becoming important tools for assistive technology, particularly through the use of motor imagery (MI) for aiding task completion. However, most existing methods of MI classification have been applied in a trial-wise fashion, with window sizes of approximately 2 s or more. Application of this type of classifier could cause a delay when switching between MI events. Approach. In this study, state-of-the-art classification methods for motor imagery are assessed offline with considerations for real-time and self-paced control, and a convolutional long-short term memory (C-LSTM) network based on filter bank common spatial patterns (FBCSP) is proposed. In addition, the effects of several methods of data augmentation on different classifiers are explored. Main results. The results of this study show that the proposed network achieves adequate results in distinguishing between different control classes, but both considered deep learning models are still less reliable than a Riemannian MDM classifier. In addition, controlled skewing of the data and the explored data augmentation methods improved the average overall accuracy of the classifiers by 14.0% and 5.3%, respectively. Significance. This manuscript is among the first to attempt combining convolutional and recurrent neural network layers for the purpose of MI classification, and is also one of the first to provide an in-depth comparison of various data augmentation methods for MI classification. In addition, all of these methods are applied on smaller windows of data and with consideration to ambient data, which provides a more realistic test bed for real-time and self-paced control.
Dynamic manoeuvres of KCS in waves using URANS computations with overset grids
Authors: Jin Yuting , Magee Allan R , Yiew Lucas J , Zheng Yingying 
Published: November 2019

Abstract
This paper presents a CFD URANS approach to model self-propelled free running maneouvres for autonomous or remote-controlled surface vessels in calm water and Stokes waves. The object of study in this paper is a benchmark container ship KCS. A hierarchy of overset grids are utilised, allowing active rudder motions while the vessel is undertaking 6 DoF turning circle and zig-zag manoeuvres. Body force propeller model (BFM) is adopted to drive the vessel at a constant approaching speed corresponds to Fr=0.26. Verification and validation study is performed for estimating the numerical uncertainties within the computations. In calm water, the computed vessel trajectories and velocities are compared against experimental data from literature and mathematical model (MM) based simulation results. Differences between URANS and experimental data are around 10.0%. After introducing waves, the manoeuvring behaviour of the vessel changes due to the presence of wave frequency loads and drift loads. The wave frequency loads exert fluctuations on measurements such as velocity, yaw rate, vessel encounted loads and etc., while the drift loads result in shift in the vessel’s trajectory especially for the turning circle manoeuvre.
Simplifying interactions between autonomous and conventional ships with e-Navigation
Authors: Porathe Thomas , Rødseth Ørnulf Jan 
Published: November 2019

Abstract
Ships in autonomous mode will for a long time interact with conventional ships with human decision-makers on the bridge. For safety it will be necessary to simplify this interaction and this paper discusses three areas which will be crucial in this respect: the collision regulations, e-navigation and traffic separation schemes. To be able to code collision avoidance algorithms COLREGS must be quantified. Soft enumerations like “good seamanship” needs to be made machine-readable. At the same time, such attempts threaten to make them less human-readable. On the positive side e-Navigation services like route exchange promises to make ship intentions more transparent and paired with an extended network of Traffic Separation Schemes future interaction between manned ships and ships in autonomous mode can be facilitated.
Projecting global urban land expansion and heat island intensification through 2050
Authors: Huang Kangning , Li Xia , Liu Xiaoping , Seto Karen C 
Published: November 2019

Abstract
Urban populations are expected to increase by 2–3 billion by 2050, but we have limited understanding of how future global urban expansion will affect urban heat island (UHI) and hence change the geographic distributions of extreme heat risks. Here we develop spatially explicit probabilistic global projections of UHI intensification due to urban land expansion through 2050. Our projections show that urban land areas are expected to expand by 0.6–1.3 million km2 between 2015 and 2050, an increase of 78%–171% over the urban footprint in 2015. This urban land expansion will result in average summer daytime and nighttime warming in air temperature of 0.5 °C–0.7 °C, up to ∼3 °C in some locations. This warming is on average about half, and sometimes up to two times, as strong as that caused by greenhouse gas (GHG) emissions (multi-model ensemble average projections in Representative Concentration Pathway 4.5). This extra urban expansion-induced warming, presented here, will increase extreme heat risks for about half of the future urban population, primarily in the tropical Global South, where existing forecasts already indicate stronger GHG emissions-warming and lack of adaptive capacity. In these vulnerable urban areas, policy interventions to restrict or redistribute urban expansion and planning strategies to mitigate UHIs are needed to reduce the wide ranges of impacts on human health, energy system, urban ecosystem, and infrastructures.