bluuebunny/crossref_metadata_2025 huggingface dataset:
Induction of Immune Response and Protective Immunity by a Local Isolated Varicella Virus in Animal Model: A Future Candidates for Vaccine Production
Authors: Esna-Ashari Fatemeh , Sabahi Farzaneh , Ravanshad Mehrdad , Mohammadi Ashraf
Published: April 2019

Preparation of the indigenous varicella zoster vaccine could significantly reduce the disease burden of varicella zoster virus especially in immunosuppressed children. To achieve this goal, the varicella zoster virus was isolated from an 8 years boy infected with chicken pox. The virus was cultivated in sensitive cell line and determined varicella zoster.
The adaptation and attenuation of virus was carried out after several passages in MRC-5 cell culture, Primary Guinea pig embryo fibroblast cell culture and again switching in MRC-5 cell culture. The challenged of vaccine dose was found 3LogCCID50. Following two doses of immunization in guinea pigs via inoculated cell culture-fluid attenuated- local isolated VZV at zero and 14 day, the humoral immune response, varicella-zoster virus (VZV) IgG and IgM were determined using enzyme-linked Immunosorbent and seroneutralization assays at 7, 14, 21, 30, 60, 90.120 days after receiving of the first and second dose of vaccine.
The results of immunization showed good 93% seroconversion in guinea pig which compared with vOKa vaccine was not significant (p<0.05).
The prepared attenuate varicella zoster virus promising a candidate Virus for our future plan to vaccine production.
MHC Class II Deficiency with Normal CD4+ T Cell Counts: A Case Report
Authors: Abolnezhadian Farhad , Saieedi-Boroujen Ali , Iranparast Sara
Published: April 2019

Major histocompatibility complex (MHC) class II deficiency is a rare primary immunodeficiency disorder (PID) with less than 200 cases worldwide. Here, we report an 8 month–old girl with MHC class II deficiency with a novel homozygous mutation in RFXANK gene (NM_001278728: exon 5: c.495G>A: p.Trp165*) and normal CD4+ T cell counts, diagnosed by whole exome sequencing (WES) and negative HLA–DR proteins on peripheral blood mononuclear cell (PBMC) in flow cytometry. She was referred with pneumonia, prolonged fever, resistance to antibiotics (ceftriaxone, clindamycin, and vancomycin), and low serum immunoglobulin (IG) levels, while natural killer (NK), B, and T cells were normal. She received intra-venous immune-globulin (IVIG) replacement, broad spectrum antibiotics, and anti-fungal treatments. The presented case report is interesting not only because of the rarity of the PID but also due to normal CD4+ T cell counts. According to our experience, we suggest that physicians consider MHC class II deficiency in families with consanguineous marriages, even with normal CD4+ T cell counts. At the first, the diagnosis of the disease could be successfully perform using WES, and finally, treatment with hematopoietic stem cell transplantation can save the patients’ lives.
The Review of in Vitro and in Vivo Studies over the Glycyrrhizic Acid as Natural Remedy Option for Treatment of Allergic Asthma
Authors: Fouladi Saloomeh , Masjedi Mohsen , Ganjalikhani Hakemi Mazdak , Eskandari Nahid
Published: April 2019

Allergic asthma is the most common type of allergy which have become increasingly prevalent in all around the world. Airway eosinophilic inflammation is a major feature of allergic asthma. Glycyrrhiza uralensis (licorice) is one of the regular herbs in traditional Chinese medicine (TCM) as it has many effects on the immune system such as anti-inflammatory and immune regulatory activity; antiviral and antitumor effects.
This review focuses on the "licorice” components, mainly glycyrrhizic acid (GA) and derivatives structure that evaluate its effects on the allergic asthma. We performed searching articles in Pubmed, Web of Science, and Scopus data bank from 1990 to 2017. The search syntax were: "glycyrrhizin" OR " glycyrrhizic acid" OR " glycyrrhizinic acid" OR" glycyrrhiza glabra" OR " liquorice root" OR "G. glabra" OR "glycyrrhizic Acid" AND "allergic asthma" OR "bronchial asthma" OR "asthma, bronchial" OR "airway hyper-responsiveness" OR "airway inflammation".  
Several molecular mechanisms and inflammatory mediators may possibly be responsible for efficacy of glycyrrhizin. Some in vitro studies indicated to the fact that possible mechanisms of anti-inflammatory effects could be through reduction of pro-inflammatory mediator's synthesis that motivates eosinophil, basophils and mast cells to release cytokines for the differentiation of T helper cells into Th2 cells to secrete interleukins.
Furthermore, some transcription factors such as NF-κB, STAT6 and HDAC2 go between modulations of anti-asthmatic effects. The last but not the least it can be said that glycyrrhizin is potentially a good herbal drug with the lower most adverse effects for asthma treatment.
The Stimulatory Effects of Medicinal Plants on β2-adrenoceptors of Tracheal Smooth Muscle
Authors: Shakeri Farzaneh , Ghorani Vahideh , Saadat Saeideh , Gholamnezhad Zahra , Hossein Boskabady Mohammad
Published: April 2019

Medicinal plants have been identified and used as primary sources in prevention and treatment of pulmonary diseases (mainly obstructive pulmonary diseases) from ancient times due to various pharmacological activities. In this review, the stimulatory effects of extracts, some fractions and constituents of medicinal plants on β2-adrenoceptors which could be used as possible therapeutic agents in the future were reviewed.
Various databases including; Medline, PubMed, ScienceDirect, Scopus, and Google Scholar were searched using stimulatory effect, β2-adrenoceptors, possible mechanism, tracheal smooth muscle (TSM), medicinal plants and their constituents as keywords from 1985 to 2017.
All studied plants including; Nigella sativa, Rosa damascena, Thymus vulgaris, Carum copticom, Carum carvi, Zataria multiflora, Crocus sativus, Cuminum cyminum, Liomnia acidissima, Portulaca oleraceae, Satureja hortensis, Ephedra sinica and Achillea millefolium showed relaxant effect on tracheal smooth muscle with a stimulatory effect on β2-adrenoceptors mechanism.
The studied plants and their constituents could be of therapeutic value in clinical practice as a bronchodilatory drug by β2-adrenoceptors stimulatory mechanism for treatment of obstructive pulmonary diseases.
Beneficial Effects of Hydroalcoholic Extract of Saffron in Alleviating Experimental Autoimmune Diabetes in C57bl/6 Mice
Authors: Faridi Shole , Delirezh Norouz , Abtahi Froushani Seyyed Meysam
Published: April 2019

Streptozocin (STZ) is a strong alkalizing agent which is capable of destroying the beta cells of the pancreatic islets. Multiple low doses (40 mg/kg, intraperitoneally for 5 consecutive days) prescription of STZ to mice can lead to the T cell-dependent immune response and induction of autoimmune diabetes (AD) with complete similarity to the human type 1 diabetes (T1D). This study has evaluated the effects of hydroalcoholic extract of saffron on the clinical and immunological profile of experimental autoimmune diabetes in C57BL/6 mice.
After the establishment of the AD, mice were treated orally with hydroalcoholic extract of saffron (500 mg/kg) for 3 weeks. The results with p<0.05 were considered significant.
Obtained data showed that treatment with the hydroalcoholic extract of saffron significantly reduced the incidence of hypoglycemia and restored insulin secretion and histopathological changes in pancreas sections. In addition, treatment with saffron reduced lymphocyte proliferation index in the cells isolated from the pancreas of diabetic mice. Also, the extract of saffron markedly decreased the production of pro-inflammatory interleukin-17 (IL-17) increased anti-inflammatory IL-10 and transforming growth factor-β in the pancreatic cell population. Moreover, the production of proinflammatory nitric oxide and reactive oxygen substances were down-regulated by the saffron extract.
It seems that the hydroalcoholic extract of saffron can be considered as a useful strategy in the treatment of type 1 diabetes.
CLIMATE CHANGE-FOOD SECURITY-FINANCIAL ASSETS NEXUS: EVIDENCE FROM INDONESIA
Authors: Yuniarti Dini , Purwaningsih Yunastiti , Soesilo AM , Suryantoro Agustinus
Published: April 2019

Purpose: The aim of the study is to investigate the position of household food security when they face climate change and examine the influence of financial asset on food security dynamic. Additionally, we investigate the impact of livelihood assets such as human capital, financial capital, social capital, natural capital, and physical capital on food security dynamic.

Methodology: There are four categories of food security dynamic namely household that always secure, improved, worse, and always food insecure. Taking the case on Kulonprogo, Yogyakarta Special Region, we use primary data with a longitudinal survey when El Nino (2015) and La Nina (2016). The sample size is 107 households of Program KeluargaHarapan’s receiver. To examine the association between financial assets and food security dynamic we used Multinomial Logit Regression.

Results: The results of the study indicates that households in the face of climate change did not experience significant changes in food security positions in both seasons (El Nińo and La Nińa). Mild food insecurity still dominates impoverished households.

Implications: Thus, the proportion of households that experienced improvement or decline was dominated by mild food insecurity. Furthermore, financial assets such as saving and credit can enhance poor household food security. Meanwhile, there are not all household livelihood assets improve food security yet; only human capital and natural capital can improve household food security. The appropriate food security strategies can be the focus on financial sector intervention program.
Analysis of Student Behaviour in Habitable Worlds Using Continuous Representation Visualization
Authors: Pardos Zachary A , Horodyskyj Lev
Published: April 2019

We introduce a novel approach to visualizing temporal clickstream behaviour in the context of a degree-satisfying online course, Habitable Worlds, offered through Arizona State University. The current practice for visualizing behaviour within a digital learning environment is to generate plots based on hand-engineered or coded features using domain knowledge. While this approach has been effective in relating behaviour to known phenomena, features crafted from domain knowledge are not likely well suited to making unfamiliar phenomena salient and thus can preclude discovery. We introduce a methodology for organically surfacing behavioural regularities from clickstream data, conducting an expert in-the-loop hyperparameter search, and identifying anticipated as well as newly discovered patterns of behaviour. While these visualization techniques have been used before in the broader machine-learning community to better understand neural networks and relationships between word vectors, we apply them to online behavioural learner data and go a step further, exploring the impact of the parameters of the model on producing tangible, non-trivial observations of behaviour that suggest pedagogical improvement to the course designers and instructors. The methodology introduced in this paper led to an improved understanding of passing and non-passing student behaviour in the course and is applicable to other datasets of clickstream activity where investigators and stakeholders wish to organically surface principal patterns of behaviour.
Diversity of Online Behaviours Associated with Physical Attendance in Lectures
Authors: Brennan Amelia , Sharma Akshay , Munguia Pablo
Published: April 2019

A common use of technology in higher education is the provision of online course materials, invoking an investigation of the ways in which students engage with online course content, and how their participation changes over time. This is particularly necessary in the context of high absenteeism from lectures, where online access may be the only way in which particular students are engaging with the course. In this study, we examine large-scale patterns of attendance in class, as well as four types of access to online materials. We define two online behavioural metrics — richness and evenness — to capture the distribution of online behaviours within 255 courses, and examine how these change over time. We find that both physical and online attendance decrease throughout the semester, but the fraction of students present online is considerably higher than the fraction present in lectures. Students adapt their online behaviour, and rare behaviours disappear over time. It is important to consider how we provide content, both face-to-face and online, in order to ensure that as many students as possible are accessing this content in ways that we intend.
From Students’ Questions to Students’ Profiles in a Blended Learning Environment
Authors: Harrak Fatima , Bouchet François , Luengo Vanda
Published: April 2019

The analysis of students’ questions can be used to improve the learning experience for both students and teacher. We investigated questions (N = 6457) asked before the class by 1st year medicine/pharmacy students on an online platform, used by professors to prepare their on-site Q&A session. Our long-term objectives are to help professors in categorizing those questions, and to provide students with feedback on the quality of their questions. To do so, first we developed a taxonomy of questions then used for an automatic annotation of the whole corpus. We identified students’ characteristics from the typology of questions they asked using K-Means algorithm over four courses. The students were clustered based on the question dimensions only. Then, we characterised the clusters by attributes not used for clustering such as the students’ grade, the attendance, the number and popularity of questions asked. Two similar clusters always appeared (lower than average students with popular questions, and higher than average students with unpopular questions). We replicated these analyses on the same courses across different years to show the possibility to predict students’ profiles online. This work shows the usefulness and the validity of our taxonomy and the relevance of this approach to identify different students’ profiles.
Book Review: Learning Analytics Explained by Niall Sclater
Authors: Colvin Cassandra
Published: April 2019

Sclater’s book Learning Analytics Explained is not unique in its goal to present a practitioner audience with a synopsis of the “what and how” of learning analytics. Throughout LA’s brief history, studies and guides have been produced recommending models and approaches for learning analytics “deployment,” as well as other short commentaries providing an overview of what exactly learning analytics is. These resources have been intended to increase awareness of the field across research and practice, and to facilitate sustainable uptake. Yet, and in spite of the high profile of these guides, the learning analytics community still finds itself lamenting a perceived low uptake of learning analytics within the higher education sector. Sclater, himself a prominent scholar and consultant in the field of learning analytics implementations, is mindful of this present juncture in learning analytics. His observations of the education sector’s rapidly growing interest in learning analytics, alongside a concomitant lack of understanding of what learning analytics actually is and could be, acted as motivations for him to write what he hopes is “a readable and informative summary of the area.”
Book Review: Quantitative Ethnography by David Williamson Shaffer
Authors: Buckingham Shum Simon
Published: April 2019

The title is provocative: Quantitative Ethnography. Those two words are rarely uttered in the same breath except in conflict! For the former to be an adjective to the latter is surely ridiculous. Yet the “quant/qual” gulf is precisely what David Williamson Shaffer seeks to bridge. His message: people, we’re all on the same side, and I’m not asking you to sacrifice the principles you hold so dearly.
Improved Photoelectrothermal Model with Thermal Parameters Variation Applied to an Extra-High Current COB LED
Authors: Pereira Dênis de C. , Tavares Pedro L. , Almeida Pedro S. , Soares Guilherme M. , Tofoli Fernando L. , Braga Henrique A. C.
Published: April 2019

This work is mainly concerned with the improved photoelectrothermal (IPET) modeling of an extra-high current (EHC)and extra-high luminous flux (up to 60 klm) solid-state light source based on a chip-on-board (COB) light-emitting diode (LED).The studied COB technology presents the particular challenge of extremely small thermal resistances, with extra-high currentlevels through the lamp (up to 12 A). Considering the unique thermal characteristics of such devices, an improved PET modelingand its respective experimental methodology are detailed. Accurate techniques are also proposed to estimate the device junction temperature.The studied method is very suitable to represent EHC COB devices, since it includes the main thermal parameters variation into a novel model,optimizing the flux prediction for this technology. In this context, the static flux and efficacy are analyzed by means of experimental testsand theoretical model, where the improvement of the employed method is highlighted.
Topology Optimization of the Turbine Disk Structure under Thermomechanical Loads
Authors: Bui V.P. , Prokopov V.S. , Gavryushin S.S. , Papazafeiropoulos G.
Published: April 2019

This article presents a study of topology optimization to obtain a new form of an axisymmetric structure using mathematical tools of solid body mechanics and finite elements analysis and taking into account the effect of thermal and mechanical loads. The problem of minimizing the compliance of a rotating turbine disk is solved sequentially, with a given of the volume constraint. First, temperature distribution is obtained in the design area, then the problem of determining the stress-strain state is solved taking into account the thermo-effect, and finally, topology optimization is performed using the moving asymptotes method. The results of calculations for different optimization scenarios are compared: operating at different volume fractions and different rotational speeds of the turbine disk; with and without thermal loading. A comparison of the optimized model obtained by implementing the developed program in the MATLAB environment, and structures created using ANSYS APDL and ABAQUS (TOSCA) is presented. The form of the optimized disk allows its manufacturing by both traditional as well as additive methods.
Editorial
Authors: Weber Alan S. , Verjee Mohamud A.
Published: April 2019

Editorial accompanying the Proceedings of the 1st International Conference on Medical Humanities in the Middle East; 2018 Nov 17-18: Doha, Qatar.
The various faces of genomics in Islamic bioethics
Authors: Ghaly Mohammed
Published: April 2019

Abstract from the Proceedings of the 1st International Conference on Medical Humanities in the Middle East; 2018 Nov 17-18: Doha, Qatar.
Witnessing cancer: The voices that accompany me
Authors: Frank Arthur W.
Published: April 2019

Abstract from the Proceedings of the 1st International Conference on Medical Humanities in the Middle East; 2018 Nov 17-18: Doha, Qatar.
Listening to your patient, a key factor for successful consultations in a clinical setting
Authors: Verjee Mohamud A.
Published: April 2019

Abstract from the Proceedings of the 1st International Conference on Medical Humanities in the Middle East; 2018 Nov 17-18: Doha, Qatar.
Narrating Arab women's voice and disability: Notes on the Flesh, a biomythography
Authors: Alshammari Shahd
Published: April 2019

Abstract from the Proceedings of the 1st International Conference on Medical Humanities in the Middle East; 2018 Nov 17-18: Doha, Qatar.
Impact of fluorescent color temperature on attention deficit hyperactivity disorder (ADHD) subjects: A FMRI study
Authors: Amor Cherif Mohamed , O'Boyle Michael , Pati Debajyoti
Published: April 2019

Abstract from the Proceedings of the 1st International Conference on Medical Humanities in the Middle East; 2018 Nov 17-18: Doha, Qatar.
The Zar (Bori) Cult: A proposed integrated psychotherapy module
Authors: Elhassan Nahid M. , Al Safi Ahmed , Khairi Abdalla A. B.
Published: April 2019

Abstract from the Proceedings of the 1st International Conference on Medical Humanities in the Middle East; 2018 Nov 17-18: Doha, Qatar.
Art therapy for grief and self-care in medical settings
Authors: Gómez-Carlier Natalia , Powell Sara
Published: April 2019

Abstract from the Proceedings of the 1st International Conference on Medical Humanities in the Middle East; 2018 Nov 17-18: Doha, Qatar.
Anatomy of Melancholy: An Arabic take on an English classic
Authors: Haddad George
Published: April 2019

Abstract from the Proceedings of the 1st International Conference on Medical Humanities in the Middle East; 2018 Nov 17-18: Doha, Qatar.
Doctors as mediators between two worlds: Biomedicine and socioeconomic realities in Arab societies (A reading through literary texts)
Authors: Hussein Faten
Published: April 2019

Abstract from the Proceedings of the 1st International Conference on Medical Humanities in the Middle East; 2018 Nov 17-18: Doha, Qatar.
Factors associated with spirit possession: A cross cultural systematic literature review
Authors: Khairi Abdalla A. B. , Abdelkareem Aisha A. , Elhusein Bushra
Published: April 2019

Abstract from the Proceedings of the 1st International Conference on Medical Humanities in the Middle East; 2018 Nov 17-18: Doha, Qatar.
A view from the cuckoo's nest: The value of teaching sociology in medical schools
Authors: Larson Adam H.
Published: April 2019

Abstract from the Proceedings of the 1st International Conference on Medical Humanities in the Middle East; 2018 Nov 17-18: Doha, Qatar.
"Sparkling Moments": Graphic medicine as a reflective tool for self-efficacy and motivation
Authors: Miller Linda
Published: April 2019

Abstract from the Proceedings of the 1st International Conference on Medical Humanities in the Middle East; 2018 Nov 17-18: Doha, Qatar.
Preparing medical students for the writing of history of present illness: Marching from short story reading and the practice of visual art
Authors: Tsai Pi-Hua
Published: April 2019

Abstract from the Proceedings of the 1st International Conference on Medical Humanities in the Middle East; 2018 Nov 17-18: Doha, Qatar.
A reflective space: Supporting local and expatriate patients, developing culturally sensitive mental health practices
Authors: Powell Sara , Gómez-Carlier Natalia
Published: April 2019

Abstract from the Proceedings of the 1st International Conference on Medical Humanities in the Middle East; 2018 Nov 17-18: Doha, Qatar.
Confidentiality, partner notification and ethical issues: A qualitative research on people living with HIV in Istanbul
Authors: Şenyürek Gamze , Ulman Yesim Isil
Published: April 2019

Abstract from the Proceedings of the 1st International Conference on Medical Humanities in the Middle East; 2018 Nov 17-18: Doha, Qatar.
Adaptación de cofias metálicas confeccionadas con dos técnicas: cera pérdida colado por centrifugación convencional e inducción
Authors: Requena Cisneros Silvio Over , Loarte Campos Micarla Yanira , Zelada Ladrón de Guevara Cinthya Cecilia , Flores Valverde Yovana Elisa , Castillo Andamayo Diana Esmeralda , Quintana del Solar Martín Gilberto
Published: April 2019

Nuevas técnicas nos están permitiendo migrar de la técnica de cera perdida colado por centrifugado convencio- nal (CPCC) a técnicas como la cera perdida colado por inducción (CPCI). Objetivos: Comparar la discrepancia marginal e interna de cofias unitarias de aleación Cobalto-Cromo (Co-Cr) sobre una línea de terminación cham- fer, confeccionadas con dos técnicas: CPCC y CPCI, determinando cual técnica tuvo mejor adaptación marginal e interna. Material y Métodos: Se fabricaron13 cofias metálicas unitarias de aleación Co-Cr para cada técnica a evaluar. Se utilizó la réplica de silicona para evaluar las discrepancias marginales e internas, cada muestra fue seccionada en cruz en sentido vestíbulo-palatino y en sentido mesio-distal, luego con un estéreomicroscopio se evaluó la zona cervical, axial y oclusal.  Resultados: Se evaluó los supuestos de normalidad con la prueba de Shapiro-Wilk. Los análisis estadísticos fueron la prueba t de Student y U Mann-Whitney. La CPCI obtuvo una menor discrepancia marginal e interna en comparación con la CPC pero no se encontró diferencias estadísti- camente significativas (p>0,05) entre ambas técnicas. Conclusiones: Aunque en la mayoría de los puntos de evaluación las cofias realizadas mediante la CPCI presento mejores valores de adaptación marginal e interna en comparación con la CPCC estos resultados sólo son valores descriptivos que no fueron concluyentes, ya que en la mayoría de los puntos evaluados no existió diferencia estadísticamente significativa (p>0,05). Observamos que la mayoría de los valores de ambas técnicas se encuentran dentro del rango clínicamente aceptable.
Innovative Data Management in Advanced Characterization: Implications for Materials Design
Authors: Romanos Nick , Kalogerini Maritini , Koumoulos Elias P. , Morozinis Athanasios , Sebastiani Marco , Charitidis Costas
Published: April 2019

This paper describes a novel methodology of data management in materials characterisation, which has as starting point the creation and usage of Data Management Plan (DMP) for scientific data in the field of materials science and engineering, followed by the development and exploitation of ontologies for the harnessing of data created through experimental techniques. The case study that is discussed here is nanoindentation, a widely used method for the determination and/or modelling of mechanical properties on a small scale.The same methodology can be applicable to a large number of techniques that produce big amount of raw data, while at the same time it can be invaluable tool for big data analysis and for the creation of an open innovation environment, where data can be accessed freely and efficiently.Aspects covered include the taxonomy and curation of data, the creation of ontology and classification about characterization techniques, the harnessing of data in open innovation environments via database construction along with the retrieval of information via algorithms. The issues of harmonization and standardization of such novel approaches are also critically discussed.Finally, the possible implications for nanomaterial design and the potential industrial impact of the new approach are described and a critical outlook is given.
Durum Wheat (Triticum durum Desf.) Origin, Cultivation, and Potential Expansion in Sub-Saharan Africa
Authors: Tidiane Sall Amadou , Chiari Tiberio , Legesse Wasihun , Seid-Ahmed Kemal , Ortiz Rodomiro , Van Ginkel Maarten , Bassi Filippo Maria
Published: April 2019

Durum wheat is an important food crop in the world and an endemic species of sub-Saharan Africa (SSA). In the highlands of Ethiopia and the oases of the South Sahara this crop has been cultivated for thousands of years. Today, smallholder farmers still cultivate it on marginal lands to assure production for their self-consumption. However, durum wheat is no longer just a staple crop for food security but it has become a major cash crop. In fact, the pasta and couscous industry currently purchase durum grain at prices 10 to 20% higher than bread wheat. Africa as a whole imports over € 4 billion per year of durum grain to provide the raw material for its food industry. Hence, African farmers could obtain a substantial share of this large market by turning their production to this crop. Here, the achievements of the durum breeding program of Ethiopia are revised to reveal a steep acceleration in variety release and adoption in the last decade. Furthermore, the variety release for Mauritania and Senegal is described to show how modern breeding methods could be used to deliver grain yields above 3 t ha-1 in seasons of just 92 days of length and daytime temperatures always above 32°C. This review describes the ability of releasing durum wheat varieties adapted to all growing conditions of SSA, from the oases of the Sahara to the highlands of Ethiopia. This potential area of expansion for durum wheat production in SSA is not linked to any breeding technology, but rather it remains dependent on the market ability to purchase these grains at a higher price to stimulate farmer adoption. The critical importance of connecting all actors along the semolina value chain is presented in the example of Oromia, Ethiopia, and that success story is then used to prompt a wider discussion on the potential of durum wheat as a crop for poverty reduction in Africa.
Maximising Classroom Environment by Blended Team-Based Teaching Approach with Continued Team Reallocation
Authors: Malekigorji Maryam
Published: April 2019

Previously, we described the initial use of Flipped Team‐Based learning (FTBL) defined as TBL approach combined with flipped classroom learning methodology, in which students previewed online lectures and applied their knowledge in different in-class activities. The purpose of the present study is to review the progress within this approach and to investigate how constant changes in team allocation can affect student’s perception regarding this modified FTBL approach. Although students showed reluctance initially to get out of their ‘comfort zone’, our findings show that learners perceived the adoption of the continued random allocation, and became accustomed to this learning approach, which finally assisted them to enhance their team-work skills and classroom performance, to develop their reflective capabilities as well as improving their rapport building skills, learning and academic performance. Learners also believed that this learning strategy that creates critical incidents can simulate their future work environment as they might be expected to work in unfamiliar situations. Therefore, the present study indicated strong support for the modified FTBL method and was seen to work exceptionally well, despite some minor problems that students can experience working in a team and/or with different teammates in every session.
Device for Measuring and Maintaining the Water’s Level in a Tank
Authors: Craiu Ionut , Fidel Nicolae , Stan Mihail-Florin , Chirescu Ramona , Ion Florian
Published: April 2019

This paper presents a device for measuring and maintaining the constant water level in a tank. The device uses a capacity sensor to measure the water level. The sensor has a DC voltage output proportional to the water level in the tank. This voltage can be used in other automation too. The water level, in percentages, is displayed on a vu meter with 8 LEDs. The circuit for maintaining the constant level consists in a comparator with hysteresis. The level of the water is adjustable, using a reference voltage from a potentiometer (marked in percentages). The level of the water is compared with the prescribed level and the difference between them commands the start/stop of the water pump which supplies the tank through a relay. The device is powered by 220 V and is isolated from the environment.
Model Blended Learning Dengan Menerapkan Experiential Learning
Authors: Ariani Diana
Published: April 2019

Artikel ini berisi ulasan model pembelajaran Blended Learning yang dirancang khusus dengan menerapkan Experiential Learning. Model yang diulas adalah Model APKL merupakan model yang diperuntukan untuk mengembangkan blended learning dengan menerapkan experiential learning. APKL itu sendiri merupakan akronim dari Analisis, Pilih, kembangkan dan Lakukan. Mengapa model ini memfokuskan pada blended learning dan tidak pada model online learning, karena dengan Blended Learning dapat memberikan pengalaman belajar secara tatap muka dikombinasikan dengan berbagai modalitas pembelajaran dan konteks aplikasi berbasis teknologi.
Anionic Surfactant and Heavy Oil Interaction during Surfactant-Steam Process
Authors: Alshaikh Murtdha , Lee Yeh Seng , Hascakir Berna
Published: April 2019

Coinjecting of steam with surfactant to recover heavy crude oil is studied. Performance production of this process is achieved through analysis of the formed emulsions which provides mechanistic understanding of crude oil and surfactant interaction in the presence of steam.

Surfactants are used to reduce the interfacial tension between water and oil. While the nonpolar tail of a surfactant stays in the oil phase, its polar side remains in the water phase. Surfactant literature is in general built on light oil reservoirs, which form mostly by nonpolar hydrocarbons. However, for high-viscosity crude, the situation can be different due to its high-polarity components. Asphaltenes and resins are known as the polar components of crude oil, while saturates and aromatics are the nonpolar. Therefore, steam and surfactant-steam flood experiments were conducted on a heavy crude oil sample with low API gravity, high viscosity, and high polar fraction content. Firstly, the crude oil sample was blended with anionic surfactant solution via magnetic stir and formed emulsion phases were characterized. To determine steam’s effects, emulsions were exposed to steam and evaluated by optical microscopy, Fourier Transform Infrared Spectroscopy, dielectric constant, and zeta potential measurements. Secondly, core flood experiments were carried on to evaluate the surfactant-steam process. Lastly, produced oil samples from two flooding tests were analyzed under optical microscopy and the impact of polarity and ionic bond interaction were investigated on produced oil, produced water, and produced polar asphaltene samples.

Dielectric constant measurements is introduced as an indirect method to determine polarity and enhance emulsion characterization for heavy crude oils. It was observed that the high amounts of asphaltenes and resins in crude oil favor emulsion formation in steam process due to polar fractions of crude oil which are known as emulsifiers. However, zeta potential measurements showed that in surfactant-steam process emulsion formation is promoted due to electrical attraction of anionic head of surfactant with inorganic surface morphology of asphaltenes.

Our results provide important information on how the surfactant-steam process can be successful in heavy oil reservoirs that consist different amounts of polar components with high inorganic content. Developing the right emulsion characterization tools such as electrical properties will assist in choosing the best surfactant candidates for different heavy crude oils with high polar components, facilitating the surfactant-steam flooding processes.
Economic Nano-Additive to Improve Cement Sealing Capability
Authors: Tabatabaei Maryam , Dahi Taleghani Arash , Alem Nasim
Published: April 2019

The primary objective of this study is introducing low-cost graphite nanoplatelets (GNPs) for oilwell cementing that improves long-term wellbore isolation and the durability of the hydrated cement. To seek this goal, we first propose two methodologies to modify the surface properties of the nano-additives to disperse them in the cement paste. There are essentially two significant incentives for the surface modification of nanoparticles: (1) a proper dispersion of nanoparticles in the slurry and (2) enhance the interaction between these nanoparticles and the cementitious matrix. It is expected that this interaction will improve the cement integrity by controlling micro-cracks initiation and their propagation. Then, experiments are conducted to assess enhanced mechanical behavior of the new cement nanocomposite.
Optimization of Immiscible Alkaline-Surfactant-Alternated-Gas/CO2 Flooding in an Upper Assam Oilfield
Authors: Phukan Ranjan , Borgohain Gogoi Subrata , Tiwari Pankaj , Singh Vadhan Ramanpreet
Published: April 2019

The immiscible alkaline-surfactant-alternated-gas/CO2 (ASAG) flooding comprise of alternately injecting alkali-surfactant (AS) formulations and gas/CO2 into the formation leading to the generation of in-situ foam. Optimization of the ASAG process is a necessary step prior to its application in a particular oil field for cost-effective enhanced oil recovery (EOR) approach. In this article, optimization of the ASAG flooding in an Upper Assam oilfield was studied through lab-scale core flood experiments. First, reservoir core samples, crude oil, and formation water of the oilfield were characterized. Second, AS formulations were designed through foam stability tests, phase behavior tests, and equilibrium interfacial tension (IFT) measurements. Third, a total of 15 lab-scale core flooding tests were conducted through different ASAG injection schemes. Crude oil of the oilfield was medium gravity with acid number equaling 2.1 mg of KOH/gm. The average porosity and permeability of core samples were found to be approximately 20% and 6 md respectively. XRD and FESEM analysis showed the presence of silica, quartz and smectite clays in the rock samples. The total salinity based on the ionic composition of the formation water was found to be 3458 ppm. The foam stability tests indicated that maximum foaming behavior in presence of crude oil occurred at specific combination of surfactant, alkali, and brine salinity. The optimal salinities determined by salinity scan were found to concur with the salinities at which lowest equilibrium IFT values were obtained for the AS formulations. The lowest IFT values were in the ultra-low range (less than 0.01 mN/m). The favorable operating parameters with best oil recovery during ASAG flooding were obtained with 1:1 slug ratio, 0.25 pore volume (PV) slug size, 0.2 ml/min gas injection rate, 2 PV injected fluid volume and combined gas-liquid tapering. The application of negative salinity gradient during ASAG flooding could further improve the additional oil recovery to 29.19 % original oil in place. Moreover, the use of a sacrificial agent during waterflooding proved to be valuable in economically improving the cumulative oil recovery by ASAG flooding.
Innovative Convolutional Neural Networks Applied in Dynamometer Cards Generation
Authors: Peng Yi , Zhao Ruidong , Zhang Xishun , Shi Junfeng , Chen Shiwen , Gan Qingming , Li Gangyao , Zhen Xiaoxiong , Han Tao
Published: April 2019

There are nearly 200,000 oil wells producing in PetroChina and 94% are sucker-rod pumping wells. Dynamometer card is essential for well diagnosis and optimization, which cost huge investment on sensor installations and maintenance. This paper present an innovative artificial intelligence method to get the card data directly from electrical parameters.

With the development of artificial intelligent technology, many challenges in oil and gas industry have the potential to be addressed by developing artificial intelligent and Big Data analytic tools. This paper presents a method to get the dynamometer card using the electrical data collected during production. In our method, we start with building our training datasets consist of dynamometer card and corresponding electrical data with various well performance conditions. We using the state of art artificial intelligent deep learning algorithm to training the data and make a general model to generate the dynamometer card from electrical data.

This method is based on image processing and deep learning, which eliminates the disadvantage of conventional physical-mechanism based model. After tested training datasets in several oilfields in PetroChina, the model demonstrates very high accuracy with almost 90% similarity to corresponding dynamometer card. The calculated dynamometer card from our model are good consistent with the field data too. In addition, this method has been testing on hundreds of wells newly produced well utilizing sucker-rod pumping system, which would reduce millions of investment on the sensors and equipment on average 5000 newly producing wells in PetroChina each year.

As a result, with the fast development of artificial intelligence technology and expanding training datasets, the deep learning method will be fully utilized in more sucker-rod pump wells to generate the dynamometer card, which is also part of the intelligent well strategy. In the low oil price trend, artificial intelligence is a good choice to lower the investment and maintenance cost for mature fields and newly produced fields.
Enhancing Reservoir Management Quality and Efficiency of Thermal Assets with Data-Driven Models
Authors: Kim Tae Hyung
Published: April 2019

Temperature monitoring is the most important surveillance in thermal assets, but temperature logging is limited in frequencies and locations. In addition, it is extremely difficult to review all the measured temperature and injection data manually since there are 10,000+ wells in Kern River field. To overcome the limitations, data-driven reservoir temperature models are presented that are built using past temperature logs and steam injection rates of the Kern River field, California.

Based on the physics and geologic understanding the reservoir, adequate input features were selected and queried. Data cleanup was conducted to remove erroneous data or fix data errors using statistical tools such as multivariate Gaussian distribution. Voronoi diagram based dynamic injector selection algorithm (DISA) was developed to correctly capture the injectors which impact on temperature changes of a temperature observation well. Based on geologic characteristics of the Kern River, reservoir was divided into two sub-reservoirs, North-East and South-West. Two full field models were developed for predicting maximum and mean temperatures of a heated zone with multi-layer perceptron for both sub-reservoirs using about 120,000 data points from over 25,000 temperature curves measured at 700+ temperature observation wells.

To estimate proper model update frequencies and verify the process, three yearly models (models 2015, 2016, and 2017) were built and validated by using one-year future temperature predictions in 2016, 2017, and 2018. For instance, model 2015 was trained with data until the end of 2015 and validated against 2016 data. Maximum temperature prediction r2 of 2017 South-West and North-East models were 0.96 and 0.98, respectively. Model 2017 has been deployed for alerting exception cases automatically and flagging abnormal temperature measurements. Also, the models improve the quality of heat injection design by providing temperature predictions based on planned heat injection rates. This novel automated workflow with data-driven models enhances reservoir management efficiency by reducing engineers’ unproductive time such as data manipulation and allowing them to focus on value-added works like analysis and optimization.
High Resolution Dynamic Drainage Height Estimations using Subsurface DNA Diagnostics
Authors: Percak-Dennett Elizabeth , Liu Joanne , Shojaei Hasan , Luke Ursell , Thomas Ishoey
Published: April 2019

Subsurface DNA Diagnostics™ is a low-risk, high-resolution evaluation tool offering oil and gas operators a measurement of fluid movement in the subsurface. DNA sequencing methodologies that use subsurface DNA markers acquired from well cuttings and produced fluids are currently used in all major US unconventional basins to elucidate drainage heights for new and existing wells. Dynamic drainage height estimations are especially important in field-wide development, when actionable turnaround time of drainage height estimates is a priority to improve subsurface understanding and maximize reservoir economics.

For this work, well cuttings were collected during drilling every 10’ MD from a 1000’ vertical section of interest in the Permian's highly stratified Wolfcamp formation. Subsurface DNA was extracted and sequenced from cuttings at the sub-formation level to create a robust DNA marker profile. Produced fluids were collected every 2 weeks through 140 days. DNA markers from each sub-formation were compared to every fluid time point using a Bayesian mixture modeling algorithm. This method produces an estimate of the relative contribution of DNA markers from each sub-formation for each fluid sample over time.

The result of Subsurface DNA Diagnostics is a novel subsurface log that characterizes DNA markers as a function of depth, and identifies the intervals with relative higher productivity compared to the other intervals over time. These drainage metrics are then overlaid with existing petrophysical properties to refine knowledge of oil and water behavior within different sub formations during a well's lifetime.

Subsurface DNA Diagnostic's use of well cuttings and produced fluids enables rapid scalability due to low-risk sampling (no downhole tools or lost production time) and minimal field personnel time. As such, an operator can relatively quickly characterize the drainage height of their field over time using several vertical baselines and a routine sampling protocol of producing wells in both exploratory, development, and producing phases of the asset.
Constrained Least-Squares Multiwell Deconvolution
Authors: Cumming J , Jaffrezic V , Whittle T , Gringarten A C
Published: April 2019

Objectives/Scoper

In this paper, we reduce non-uniqueness and ensure physically feasible results in multiwell deconvolution by incorporating constraints and knowledge to the methodology of Cumming et al. (2014). The constraints discourage non-physical shapes for the deconvolved derivatives and improve solution quality. We also encode knowledge on the reservoir, for instance, if it is a closed system, we impose that all deconvolved derivatives should tend towards a common unit slope at some future time.

Methods, Procedures, Process

Single-well deconvolution (von Schroeter, Hollaender and Gringarten, 2001, 2004) transforms variable-rate pressure data from a well test, into a single constant-rate drawdown with the same duration as the pressure history. The resulting deconvolved derivative shows features not visible within the durations of any of the test build up or drawdown periods and therefore enhance analysis and interpretation. Single-well deconvolution, however, is applicable only to individual isolated wells. Multiwell deconvolution - introduced by Levitan (2006) and developed by Cumming et al. (2013) - generalises the solution methodology to the problem of multiple wells within the same connected system.

Results, Observations, Conclusions

Multiwell deconvolution yields not only the constant-rate deconvolved derivatives for every well in the system, but also the interference effects from any one well to any other. These interference effects provide valuable information concerning storativity and connectivity within the reservoir, which is not accessible otherwise. Multiwell deconvolution is, however, an overdetermined problem and may therefore yield non-unique solutions that can reproduce pressure histories to a similar degree of precision, but correspond to different, potentially conflicting, and possibly non-physical responses and interpretations. This non-uniqueness and the possibility of non-physical solutions need to be reduced for practical multiwell deconvolution of field data.

Novel/Additive Information

We demonstrate how a combination of constraints on the shapes of the deconvolved derivatives and knowledge of the reservoir results in an improved level of quality and consistency in multiwell deconvolution solutions. We illustrate this new constrained least-squares multiwell deconvolution approach with synthetic examples with known solutions involving up to nine wells.