bluuebunny/crossref_metadata_2025_split huggingface dataset:
Effects of the Chinese herbal formula San-Huang Gu-Ben Zhi-Ke treatment on stable chronic obstructive pulmonary disease: study protocol of a randomized, double-blind, placebo-controlled trial
Authors: Zu Yaqi , Li Demin , Lei Xiang , Zhang Hongchun 
Published: November 2019

Abstract
Background
Due to the large number of patients, high mortality rate as well as high social costs and economic burden, chronic obstructive pulmonary disease (COPD) has become one of the most important health problems around the world, which has attracted people’s attention. Currently, Chinese herbs have been widely used as alternative medicine (CAM) for COPD patients. The Chinese herbal formula San-Huang Gu-Ben Zhi-Ke (SHGBZK) has shown good clinical efficacy in COPD in preclinical studies. Animal experiments have shown that it has mucosal immune barrier function and can maintain airway wall integrity, reduce inflammatory cell infiltration, promote inflammatory damage repair, and relieve narrow airway conditions.

Methods/design
This study is a randomized, double-blind, placebo-controlled trial. A total of 100 patients with stable COPD diagnosed with deficiency of lung qi and spleen qi will be recruited and randomly assigned to one of two treatment groups: SHGBZK treatment, N = 50; placebo treatment, N = 50. The two groups will receive basic treatment for COPD according to the 2017 GOLD Guidelines for Chronic Obstructive Pulmonary Disease. Patients will stick to the treatment they used to take as much as possible, and will be given present general treatment when acute exacerbation of COPD occurs during the study. Both groups will receive a 24-week intervention and patient status will be assessed at 24 weeks and then 28 weeks after treatment. After the 24-week treatment, patients will be followed up for another 28 weeks. Outcome measures, including the frequency and duration of acute exacerbation, lung function, traditional Chinese medicine symptom score, exercise capacity, and quality of life will be assessed.

Discussion
It is hypothesized that SHGBZK will have beneficial effects in reducing the frequency and duration of acute exacerbations, improving the exercise capacity function of patients with stable COPD diagnosed with a deficiencies in lung qi and spleen qi. This study may establish a new treatment method for COPD patients, differentiating it from other drugs in clinical use used for similar clinical indications.

Trial registration
Chinese Clinical Trial Registry, ChiCTR1800016349. Registered on 26 May 2018.
Modelling temporal dynamics of Culicoides Latreille (Diptera: Ceratopogonidae) populations on Reunion Island (Indian Ocean), vectors of viruses of veterinary importance
Authors: Grimaud Yannick , Guis Hélène , Chiroleu Frédéric , Boucher Floriane , Tran Annelise , Rakotoarivony Ignace , Duhayon Maxime , Cêtre-Sossah Catherine , Esnault Olivier , Cardinale Eric , Garros Claire 
Published: November 2019

AbstractBackgroundReunion Island regularly faces outbreaks of epizootic haemorrhagic disease (EHD) and bluetongue (BT), two viral diseases transmitted by haematophagous midges of the genusCulicoides(Diptera: Ceratopogonidae) to ruminants. To date, five species ofCulicoidesare recorded in Reunion Island in which the first two are proven vector species:Culicoides bolitinos,C. imicola,C. enderleini,C. grahamiiandC. kibatiensis. Meteorological and environmental factors can severely constrainCulicoidespopulations and activities and thereby affect dispersion and intensity of transmission ofCulicoides-borne viruses. The aim of this study was to describe and predict the temporal dynamics of allCulicoidesspecies present in Reunion Island.MethodsBetween 2016 and 2018, 55 biweeklyCulicoidescatches using Onderstepoort Veterinary Institute traps were set up in 11 sites. A hurdle model (i.e. a presence/absence model combined with an abundance model) was developed for each species in order to determine meteorological and environmental drivers of presence and abundance ofCulicoides.ResultsAbundance displayed very strong heterogeneity between sites. AverageCulicoidescatch per site per night ranged from 4 to 45,875 individuals.Culicoides imicolawas dominant at low altitude andC. kibatiensisat high altitude. A marked seasonality was observed for the three other species with annual variations. Twelve groups of variables were tested. It was found that presence and/or abundance of all fiveCulicoidesspecies were driven by common parameters: rain, temperature, vegetation index, forested environment and host density. Other parameters such as wind speed and farm building opening size governed abundance level of some species. In addition,Culicoidespopulations were also affected by meteorological parameters and/or vegetation index with different lags of time, suggesting an impact on immature stages. Taking into account all the parameters for the final hurdle model, the error rate by Normalized Root mean Square Error ranged from 4.4 to 8.5%.ConclusionsTo our knowledge, this is the first study to modelCulicoidespopulation dynamics in Reunion Island. In the absence of vaccination and vector control strategies, determining periods of high abundance ofCulicoidesis a crucial first step towards identifying periods at high risk of transmission for the two economically important viruses they transmit.
A distinct gut microbiota composition in patients with ankylosing spondylitis is associated with increased levels of fecal calprotectin
Authors: Klingberg Eva , Magnusson Maria K. , Strid Hans , Deminger Anna , Ståhl Arne , Sundin Johanna , Simrén Magnus , Carlsten Hans , Öhman Lena , Forsblad-d’Elia Helena 
Published: November 2019

Abstract
Background
Ankylosing spondylitis (AS) shares many characteristics with inflammatory bowel disease (IBD). Intestinal microbiota most likely plays an important role in the development of IBDs and may also be involved in the pathogenesis of AS. We aimed to define and compare the fecal microbiota composition in patients with AS, ulcerative colitis (UC), and healthy controls (HC) and to determine relationships between fecal microbiota, fecal calprotectin, and disease-related variables in AS.

Methods
Fecal microbiota composition was assessed with GA-map™ Dysbiosis Test (Genetic Analysis, Oslo, Norway), which also reports the degree of deviation of the microbiota composition compared with a healthy control population, a Dysbiosis Index (DI) score 1–5. The AS patients were assessed with questionnaires, back mobility tests, fecal calprotectin, erythrocyte sedimentation rate (ESR), and C-reactive protein (CRP).

Results
Totally, 150 patients with AS (55% men, median age 55.5 years, median BASDAI 3.2), 18 patients with UC (56% men, median age 30.5 years), and 17 HC (65% men, median age 22 years) were included. Principal component analysis showed highly separate clustering of fecal microbiota from the patients with AS, UC, and HC. Compared with HC, fecal microbiota in AS was characterized by a higher abundance of Proteobacteria, Enterobacteriaceae, Bacilli, Streptococcus species, and Actinobacteria, but lower abundance of Bacteroides and Lachnospiraceae.
Further, fecal microbiota composition differed between patients with normal (≤ 50 mg/kg, n = 57) and increased (≥ 200 mg/kg, n = 36) fecal calprotectin. Patients with increased fecal calprotectin had lower abundance of bacteria with anti-inflammatory properties such as Faecalibacterium prausnitzii and Clostridium and higher abundance of the genus Streptococcus. No association was found between the fecal microbiota composition and HLAB27 status, disease activity, function, or medication. Dysbiosis (defined as DI ≥ 3) was found in 87% of AS patients.

Conclusions
Patients with AS have a distinct fecal microbiota signature, which is linked to fecal calprotectin levels, a marker of intestinal inflammation, but not to other clinical parameters. These findings suggest a local interplay between intestinal microbiota and gut inflammation in AS.

Trial registration
ClinicalTrials.gov, NCT00858819. Registered March 9, 2009.
Semantic connection set-based massive RDF data query processing in Spark environment
Authors: Xu Jiuyun , Zhang Chao 
Published: November 2019

AbstractResource Description Framework (RDF) is a data representation of the Semantic Web, and its data volume is growing rapidly. Cloud-based systems provide a rich platform for managing RDF data. However, there is a performance challenge in the distributed environment when RDF queries, which contain multiple join operations, such as network reshuffle and memory overhead, are processed. To get over this challenge, this paper proposes a Spark-based RDF query architecture, which is based on Semantic Connection Set (SCS). First of all, the proposed Spark-based query architecture adopts the mechanism of re-partitioning class data based on vertical partitioning, which can reduce memory overhead and spend up index data. Secondly, a method for generating query plans based on semantic connection set is proposed in this paper. In addition, some statistics and broadcast variable optimization strategies are introduced to reduce shuffling and data communication costs. The experiments of this paper are based on the latest SPARQLGX on the Spark platform RDF system. Two synthetic benchmarks are used to evaluate the query. The experiment results illustrate that the proposed approach in this paper is more efficient in data search than contrast systems.
A new Internet of Things architecture for real-time prediction of various diseases using machine learning on big data environment
Authors: Ed-daoudy Abderrahmane , Maalmi Khalil 
Published: November 2019

AbstractA number of technologies enabled by Internet of Thing (IoT) have been used for the prevention of various chronic diseases, continuous and real-time tracking system is a particularly important one. Wearable medical devices with sensor, health cloud and mobile applications have continuously generating a huge amount of data which is often called as streaming big data. Due to the higher speed of the data generation, it is difficult to collect, process and analyze such massive data in real-time in order to perform real-time actions in case of emergencies and extracting hidden value. using traditional methods which are limited and time-consuming. Therefore, there is a significant need to real-time big data stream processing to ensure an effective and scalable solution. In order to overcome this issue, this work proposes a new architecture for real-time health status prediction and analytics system using big data technologies. The system focus on applying distributed machine learning model on streaming health data events ingested to Spark streaming through Kafka topics. Firstly, we transform the standard decision tree (DT) (C4.5) algorithm into a parallel, distributed, scalable and fast DT using Spark instead of Hadoop MapReduce which becomes limited for real-time computing. Secondly, this model is applied to streaming data coming from distributed sources of various diseases to predict health status. Based on several input attributes, the system predicts health status, send an alert message to care providers and store the details in a distributed database to perform health data analytics and stream reporting. We measure the performance of Spark DT against traditional machine learning tools including Weka. Finally, performance evaluation parameters such as throughput and execution time are calculated to show the effectiveness of the proposed architecture. The experimental results show that the proposed system is able to effectively process and predict real-time and massive amount of medical data enabled by IoT from distributed and various diseases.
A One Health perspective to identify environmental factors that affect Rift Valley fever transmission in Gezira state, Central Sudan
Authors: Bashir Rania Salah Eldien , Hassan Osama Ahmed 
Published: November 2019

AbstractBackgroundRift Valley fever (RVF) is a zoonotic viral vector-borne disease that affects both animals and humans and leads to severe economic consequences. RVF outbreaks are triggered by a favorable environment and flooding, which enable mosquitoes to proliferate and spread the virus further. RVF is endemic to Africa and has spread to Saudi Arabia and Yemen. There is great concern that RVF may spread to previously unaffected geographic regions due to climate change. We aimed to better understand the spatiotemporal pattern of the 2007 RVF outbreak at the human–animal–environment interface and to determine environmental factors that may have effects on RVF occurrence in Gezira state, Sudan.Materials and methodsWe compiled epidemiological, environmental, and spatiotemporal data across time and space using remote sensing and a geographical information system (GIS). The epidemiological data included 430 RVF human cases as well as human and animal population demographic data for each locality. The cases were collected from 41 locations in Gezira state. The environmental data represent classified land cover during 2007, the year of the RVF outbreak, and the average of the Normalized Difference Vegetation Index (NDVI) for 6 months of 2007 is compared with those of 2010 and 2014, when there was no RVF outbreak. To determine the effect of the environmental factors such as NDVI, soil type, and RVF case’s location on the Blue Nile riverbank on RVF incidence in Gezira state, a multilevel logistic regression model was carried out.ResultsWe found that the outbreak in Gezira state occurred as a result of interaction among animals, humans, and the environment. The multilevel logistic regression model (F = 43,858, df = 3,p = 0.000) explained 23% of the variance in RVF incidence due to the explanatory variables. Notably, soil type (β = 0.613,t = 11.284,p = 0.000) and NDVI (β = − 0.165,t = − 3.254,p = 0.001) were the explanatory environmental factors that had significant effects on RVF incidence in 2007 in Gezira state, Sudan.ConclusionsPrecise remote sensing and the GIS technique, which rely on environmental indices such as NDVI and soil type that are satellite-derived, can contribute to establishing an early warning system for RVF in Sudan.Future preparedness and strengthening the capacity of regional laboratories are necessary for early notification of outbreaks in animals and humans.
Development of the human placenta
Authors: Turco Margherita Y. , Moffett Ashley 
Published: November 2019

ABSTRACT
The placenta is essential for normal in utero development in mammals. In humans, defective placental formation underpins common pregnancy disorders such as pre-eclampsia and fetal growth restriction. The great variation in placental types across mammals means that animal models have been of limited use in understanding human placental development. However, new tools for studying human placental development, including 3D organoids, stem cell culture systems and single cell RNA sequencing, have brought new insights into this field. Here, we review the morphological, molecular and functional aspects of human placental formation, with a focus on the defining cell of the placenta – the trophoblast.
Investment in a Smaller World: The Implications of Air Travel for Investors and Firms
Authors: Da Zhi , Gurun Umit G. , Li Bin , Warachka Mitch 
Published: November 2019

A large literature reports that proximity influences investment. We extend the measurement of proximity beyond distance and report that air travel reduces local investment bias. This result is confirmed using the initiation of connecting flights through recently opened air hubs because investment at destinations served by these connecting flights increases after, not before, their initiation. Air travel also broadens the investor base of firms and lowers their cost of equity by approximately 1%. Overall, air travel improves the diversification of investor portfolios and lowers the cost of equity for firms. This paper was accepted by Tyler Shumway, finance.
Pemanfaatan Minyak Goreng Bekas Menjadi Sabun Serai
Authors: Prihanto Antonius , Irawan Bambang 
Published: November 2019

Telah dilakukan penelitian Pemanfaatan Minyak Goreng Bekas Menjadi Sabun Serai. Penelitian ini merupakan upaya untuk memanfaatkan limbah minyak goreng bekas menjadi sabun serai. Upaya untuk memanfaatkan minyak goreng bekas menjadi sabun serai ini melalui rekayasa proses. Penelitian ini dilakukan untuk mengkaji pengaruh kadar minyak serai terhadap kualitas produk sabun serai. Penelitian ini terdiri dari dua tahap yaitu tahap persiapan dan tahap pembuatan sabun serai, Pada tahap persiapan, minyak goreng bekas dibersihkan dari pengotornya melalui proses filtrasi. Minyak goreng yang telah bebas dari pengotornya selanjutnya dijernihkan melaui proses penetralan dengan larutan NaOH. Minyak goreng bekas yang telah jernih selanjutnya direaksikan dengan larutan NaOH 40 % pada suhu 55 oC dengan variasi kadar minyak serai 5 %, 7,5 %, 10%. 12.5 % dan 15 %. Hasil penelitian menunjukkan bahwa pembuatan sabun serai dari minyak goreng bekas dengan kadar minyak serai 7,5 % hingga 15 % telah memenuhi syarat sebagai sabun mandi menurut SNI. Pada konsentrasi minyak serai 15 % menghasilkan sabun serai dengan aroma serai paling kuat. Research has been conducted on Utilizing Used Cooking Oil into Lemongrass Soap. This research is an attempt to utilize used cooking oil waste into lemongrass soap. Efforts to utilize used cooking oil into lemongrass soap through process engineering. This research was conducted to examine the effect of citronella oil levels on the quality of lemongrass soap products. This research consists of two stages, namely the preparation stage and the stage of making lemongrass soap. In the preparation stage, used cooking oil is cleaned from its impurities through a filtration process. Cooking oil that has been free from the impurities is then purified through the neutralization process with NaOH solution. Clear, used cooking oil is then reacted with 40% NaOH solution at 55 oC with variations in citronella oil content of 5%, 7.5%, 10%. 12.5% and 15%. The results showed that the manufacture of lemongrass soap from used cooking oil with 7.5% to 15% citronella oil content fulfilled the requirements as bath soap according to SNI. At a concentration of 15% lemongrass oil produces lemongrass soap with the strongest lemongrass aroma.
Experimental difficulties often encountered with sludge rheological properties determination and advices to perform reliable measurements
Authors: Thiène Oumar , Dieudé-Fauvel Emilie , Baudez Jean-Christophe 
Published: November 2019

Abstract
Rheological parameters being of great importance for sludge process management, they are increasingly studied. However, experimental procedures may strongly impact their determination. Sample volume, measuring device depth and roughness but also mechanical history, have to be well-controlled to ensure reproducible results. Indeed, even if shear history can be erased with a sufficient preshear for diluted sludge, this paper clearly established that no steady state can be achieved for concentrated sludge. The longer the shear history, the lower the rheological characteristics: Reproducible results are hardly obtained.
More importantly, slippage appeared to occur even with surfaces of moderate roughness and the phenomenon is all the more important that the dry matter is high.
From all these observations, an experimental procedure based on the control of preshear and rest periods has been defined. Advices and precautions to observe are given in order to ensure reproducible and obtain unaltered results.
Legendre Collocation Method for Volterra Integro-Differential Algebraic Equation
Authors: Wei Yunxia , Chen Yanping , Huang Yunqing 
Published: November 2019

Abstract
In this work we study the numerical solution to the Volterra integro-differential algebraic equation. Two numerical examples based on the Legendre collocation scheme are designed. It follows from the convergence proof and numerical experiments
that the errors of the approximate solution and the errors of the approximate derivative of the solution
decay exponentially.
A Position-Independent Reflection-Only Method for Complex Permittivity and Permeability Determination with One Sample
Authors: Yang Chuang 
Published: November 2019

AbstractThis paper presents a position-independent reflection-only method for determining complex permittivity and permeability of a sample. In this method, both the short and match calibration kits are used to measure the reflection coefficients. Only one sample positioned arbitrarily is measured using a one-port vector network analyzer (VNA), while the complex permittivity and permeability of the sample are determined simultaneously. Experimental results in X-band for the Acrylonitrile Butadiene Styrene plastic (ABS) are included to exhibit the validity of the proposed method. The results show that the complex permittivity and permeability determined by the proposed method have a good agreement with the parameters determined by the well-known Nicolson–Ross–Weir (NRW) method. In addition, a magnetic material is simulated to further validate the proposed method.
Continuous support for rehabilitation using machine learning
Authors: Philipp Patrick , Merkle Nicole , Gand Kai , Gißke Carola 
Published: November 2019

AbstractProviding a suitable rehabilitation at home after an acute episode or a chronic disease is a major issue as it helps people to live independently and enhance their quality of life. However, as the rehabilitation period usually lasts some months, the continuity of care is often interrupted in the transition from the hospital to the home. Relieving the healthcare system and personalizing the care or even bringing care to the patients’ home to a greater extent is, in consequence, the superior need. This is why we propose to make use of information technology to come to participatory design driven by users needs and the personalisation of the care pathways enabled by technology. To allow this, patient rehabilitation at home needs to be supported by automatic decision-making, as physicians cannot constantly supervise the rehabilitation process. Thus, we need computer-assisted patient rehabilitation, which monitors the fitness of the current patient plan to detect sub-optimality, proposes personalised changes for a patient and eventually generalizes over patients and proposes better initial plans. Therefore, we will explain the use case of patient rehabilitation at home, the basic challenges in this field and machine learning applications that could address these challenges by technical means.
Preparation of spherical aminopropyl-functionalized MCM-41 and its application in removal of Pb(II) ion from aqueous solution
Authors: Lin Yi , Xu Jinjia , Sudhakar Bhosale Sanjana , Gu Junjie , Hong Ruoyu 
Published: November 2019

Abstract
Mesoporous silica microspheres were prepared by the polymerization-induced colloid aggregation (PICA) and pseudomorphic synthesis methods. The prepared microspheres have high specific surface area and MCM-41 type structure. In the PICA process, acidic silica sol was utilized as silica source and the effect of molar ration (formaldehyde/urea) was investigated. Moreover, the influences of reaction time and temperature were also studied. The specific surface area of porous and mesoporous silica microspheres were 186.4 m2/g and 900.4 m2/g, respectively. The materials were characterized by SAXS, FTIR, SEM, TEM and nitrogen sorption measurements. The prepared silica microspheres were functionalized by (3-Aminopropyl)triethoxysilane and then used to remove the lead from aqueous solution. The result indicates that the grafted silica microspheres have rapid adsorption capacity and good reproducibility. The adsorption data was fitted well with the Langmuir isotherm model, and the maximum adsorption capacities for MCM-41 silica microspheres were 102.7 mg/g.