bluuebunny/crossref_metadata_2025 huggingface dataset:
« Contre tous les pouvoirs »
Authors: Paris Myriam
Published: July 2020

« Contre tous les pouvoirs, d’une classe sur l’autre, d’une race sur l’autre, d’un sexe sur l’autre », écrit en 1979 une militante de l’Union générale des travailleurs réunionnais en France, organisation fondée en 1963 par des Réunionnais anticoloniaux exilés en France. Rassemblées dans le « groupe femmes » de cette formation, des militantes rendent compte de leurs réflexions et de leurs actions dans la presse. À partir de l’analyse d’archives militantes, au croisement de l’histoire et de la sociologie des migrations, des mouvements sociaux et du militantisme, cet article retrace l’histoire d’une mobilisation féministe intersectionnelle menée en France par des migrantes réunionnaises au cours des années 1960 et 1970.
Leadership in Serving the Public's Health
Authors: Bleich Michael R.
Published: July 2020

Building on a premise that core public health principles advance leadership capabilities across sectors, the case for linking leadership to public health is made. With public health references, leadership topics are presented that address eight domains.

[
J Contin Educ Nurs
. 2020;51(8):352–354.]
Bridging the Gap: A Hospice Nurse Residency Program
Authors: Lysaght Hurley Susan , Welsh Diane M. , Roy Kaveri M. , Godzik Cassandra
Published: July 2020

There are few formal training opportunities that exist for RNs interested in the rapidly growing field of hospice and palliative care. To address this, the curriculum for a nurse residency program was developed and delivered to 12 nurses over 1 year. The nurse residents, as well as their clinical supervisors and interprofessional colleagues, were surveyed to obtain feedback on the overall program. Skill acquisition of the nurses was also assessed. The results indicate that the nurse residents had increased levels of confidence in caring for dying patients, communication with other clinicians, and delegation and management of treatment teams and families. According to supervisors and colleagues, strengths of the program included support for new nurses, integration of the interprofessional team, and solid preparation for new hospice nurses. These findings provide nursing educators and administrators with needed insight into the development and evaluation of an RN residency program in hospice and palliative care.

[
J Contin Educ Nurs
. 2020;51(8):371–376.]
Effects of Education on Nurses' Knowledge and Attitudes of Pain Management in a Postoperative Cardiovascular Unit
Authors: Shondell LeeAnn , Foli Karen J. , Erler Cheryl
Published: July 2020

Background:

This project explores the impact of an educational in-service on nurses' knowledge and attitudes toward pain on a postoperative cardiovascular unit.

Method:

A convenience sample of nurses employed on the postoperative cardiovascular intensive care unit (
n
= 82) were asked to participate in this project, with 74 nurses attending the in-service training. Surveys that were 70% complete were used for analysis (preeducation,
n
= 22; posteducation,
n
= 24).

Results:

The results from this project demonstrated that the use of a brief educational in-service is effective and efficient in increasing nurses' knowledge and attitudes related to pain management in this group of nurses. Posteducation survey scores were significantly higher than preeducation survey scores (
p
< .001).

Conclusion:

These findings suggest that a brief educational in-service on pain management can improve nurses' knowledge and attitudes on pain management in this postoperative cardiovascular unit.

[
J Contin Educ Nurs
. 2020;51(8):377–383.]
Comparing Factors Associated With eHealth Literacy Between Young and Older Adults
Authors: Yang Eunjin , Chang Sun Ju , Ryu Hyunju , Kim Hee Jung , Jang Sun Joo
Published: July 2020

The purpose of the current study was to compare the factors associated with adults' eHealth literacy, which is vital for health consumers. A secondary data analysis was conducted with data collected from November 2017 to February 2018 for a project on the development of a Korean version of the eHealth Literacy Scale. Participants were recruited through an online survey for young adults (
n
= 210, mean age = 25.5 [
SD
= 4.7] years) and a face-to-face survey for older adults (
n
= 187, mean age = 73.2 [
SD
= 4.8] years). Hierarchical multiple regression analyses were used to analyze data and determine eHealth literacy predictors. Older adults held more positive attitudes toward internet health information than young adults (mean = 16.49 [
SD
= 2.54] and 17.04 [
SD
= 2.41], respectively;
p
= 0.029); however, eHealth literacy levels were comparable (mean = 30.50 [
SD
= 4.62] and 30.95 [
SD
= 4.17], respectively;
p
= 0.305). Attitude toward internet health information was a significant predictor of eHealth literacy in both groups, and age was only a predictor among young adults. These results elucidate predictors of eHealth literacy and inform strategies to improve eHealth literacy among young and older adults. [
Journal of Gerontological Nursing, 46
(8), 46–56.]
Demographic Factors as Determinants of E-Government Adoption
Authors: Abu-Shanab Emad Ahmed
Published: July 2020

E-government services are important aspects of today's wellbeing of citizens. The adoption of technology is explored utilizing many theories and predictors. The theory of reasoned action (TRA) proposes that perceived usefulness, perceived ease of use, and subjective norms are significant predictors of behavioral intentions. This study extended the theory with trust, and hypothesized that demographic factors (gender, age, education, and experience) are significant moderators of the relationships assumed in the research model. Responses from 699 Jordanians fully supported the suggested research model, where BI to use e-government services was significantly predicted by all proposed variables. All four demographic factors failed to be significant predictors of BI, and only two relationships were moderated by age and education. In addition, an ANOVA test concluded that means differences existed within categories of sample based on specific variables of the model. The complete results and findings and conclusions are deliberated at the end of this chapter.
Contemporary Usage of Farm Management Information Systems in Nigeria
Authors: Vajjhala Narasimha Rao , Strang Kenneth David , Bitrus Nankyer Sarah
Published: July 2020

Agriculture is a critical sector in the Nigerian economy, contributing significantly to GDP as well as employment generation. Agricultural technology has evolved substantially over the last decade with significant advancements in farm management information systems (FMIS) as well as agricultural information systems (AIS). FMIS have evolved from addressing simple production tasks to handling complex across multifunctional sectors in farming enterprises. However, the adoption rates of FMIS have been low in Nigeria. In this chapter, the contemporary usage of farm management information systems in central Nigeria is examined, and the various constraints leading to the low adoption rates are explored. In this study, the factors impacting the FMIS adoption by rural farmers in central Nigeria were examined. The findings of this study indicated that some of the demographic factors were influencing the FMIS adoption by rural farmers in central Nigeria. The results of this study in this chapter should help policymakers in framing policies intended to improve FMIS adoption rates in Nigeria.
Exploring Factors in Determining E-Banking Adoption Among Bruneian Corporate Customers
Authors: Seyal Afzaal H.
Published: July 2020

The purpose of this chapter is to investigate the significant factors that contribute towards the adoption and use of e-banking in Brunei. The study focuses on 150 corporate customers of major banks in Brunei Darussalam to explore the behavioral intent of the corporate customers toward e-banking through their attitudes. The conceptual framework was developed through theory of planned behavior (TPB) to understand the intention towards using e-banking. The data was analyzed using SPSS version 21 and PLS smart graph suggests that customers' attitudes toward e-banking is a significant predictor of behavioral intention whereas subjective norms and perceived behavioral control remained insignificant. The model has good parsimony with 52% of the total variance in intention is shared by these independent variables. However, use of e-banking was further supported by the behavioral intention. Based upon conclusion, the study provides the practical implications both for the management and researchers.
The Use of ICTs in Second Language Education
Authors: Toprak Yildiz Tugba Elif
Published: July 2020

As many aspects of our lives have been increasingly digitized, education has likewise taken its share from this digitization. Consequently, information and communication technologies (ICTs) have been progressively incorporated into education to improve the effectiveness of educational practices in formal and informal educational settings. ICTs hold great promise for second language education since they have the potential of providing language learners with increased opportunities to engage with the target language and culture even with a mouse click or a tap on their smartphones. This chapter presents an overview of how ICTs have been employed in the field of second language education over the decades by specifically elaborating on the rationale behind ICT adoption, the properties of ICTs utilized, advantages and disadvantages of ICT adoption in the field, and factors that might impede or facilitate ICT adoption in second language education. The chapter concludes with practical considerations that might affect the efficiency of ICT adoption in second language education.
Large-Scale Data Streaming in Fog Computing and Its Applications
Authors: Sharma Oshin , S. Anusha
Published: July 2020

The emerging trends in fog computing have increased the interests and focus in both industry and academia. Fog computing extends cloud computing facilities like the storage, networking, and computation towards the edge of networks wherein it offloads the cloud data centres and reduces the latency of providing services to the users. This paradigm is like cloud in terms of data, storage, application, and computation services, except with a fundamental difference: it is decentralized. Furthermore, these fog systems can process huge amounts of data locally and can be installed on hardware of different types. These characteristics make fog suitable for time- and location-based applications like internet of things (IoT) devices which can process large amounts of data. In this chapter, the authors present fog data streaming, its architecture, and various applications.
Large-Scale Data Storage Scheme in Blockchain Ledger Using IPFS and NoSQL
Authors: Kumar Randhir , Tripathi Rakesh
Published: July 2020

The future applications of blockchain are expected to serve millions of users. To provide variety of services to the users, using underlying technology has to consider large-scale storage and assessment behind the scene. Most of the current applications of blockchain are working either on simulators or via small blockchain network. However, the storage issue in the real world is unpredictable. To address the issue of large-scale data storage, the authors have introduced the data storage scheme in blockchain (DSSB). The storage model executes behind the blockchain ledger to store large-scale data. In DSSB, they have used hybrid storage model using IPFS and MongoDB(NoSQL) in order to provide efficient storage for large-scale data in blockchain. In this storage model, they have maintained the content-addressed hash of the transactions on blockchain network to ensure provenance. In DSSB, they are storing the original data (large-scale data) into MongoDB and IPFS. The DSSB model not only provides efficient storage of large-scale data but also provides storage size reduction of blockchain ledger.
Application of Deep Learning in Biological Big Data Analysis
Authors: Shukla Rohit , Yadav Arvind Kumar , Singh Tiratha Raj
Published: July 2020

The meaningful data extraction from the biological big data or omics data is a remaining challenge in bioinformatics. The deep learning methods, which can be used for the prediction of hidden information from the biological data, are widely used in the industry and academia. The authors have discussed the similarity and differences in the widely utilized models in deep learning studies. They first discussed the basic structure of various models followed by their applications in biological perspective. They have also discussed the suggestions and limitations of deep learning. They expect that this chapter can serve as significant perspective for continuous development of its theory, algorithm, and application in the established bioinformatics domain.
Integrating Blockchain and IoT in Supply Chain Management
Authors: S. Madumidha , P. SivaRanjani , B. Venmuhilan
Published: July 2020

Internet of things(IoT) is the conception of interfacing the devices to the internet to make life more efficient. It comprises the large amount of data in its network where it fails to assure complete security in the network. Blockchain is a distributed ledger where it mainly focuses on the data security. Every block in the blockchain network is connected to its next block, which prevents threats like large data loss. In the area of agri-food supply chain, where IoT plays a very important role, there occurs data integrity issues or data tampering. This can lead to improper supply chain management, timely shortage of goods, food spoilage, etc. So the traceability of agri-food supply chain is necessary to ensure food safety and to increase the trust between all stakeholders and consumers. Many illegal activities can be prevented, and cold chain monitoring can be achieved by bringing in transparency and traceability.
Emerging Information Technology Scenarios and Their Contributions in Reinventing Future Healthcare Systems
Authors: A. Reyana , V. T. Krishnaprasath , A. Suresh
Published: July 2020

Critical health information is gathered, compiled, and analysed from image scanning, laboratory testing reports, health trackers, etc. Healthcare requires a support of real-time digital information for effective decision making. As industries bring better care to consumer health systems, providers achieve their goal in delivering better diagnosis and efficient treatment to consumers. This chapter contributes to the major health components—content, infrastructure, analytics, communication, and interfaces—forming the core of all health IT. The challenge is further exaggerated on the current issues related to health data and the contribution of IT systems in healthcare management. Further, the scenarios on intelligent care systems that are capable of early diagnosis are described. This impacts the future of global healthcare services by rapidly increasing the development and bridging the gap between the personal and relevant datasets creating a new era in the world of healthcare.
Importance of Automation and Next-Generation IoT in Smart Healthcare
Authors: Alenezi Ahmed , Irfan Ahamed M. S.
Published: July 2020

Generally, the sensors employed in healthcare are used for real-time monitoring of patients, such devices are termed IoT-driven sensors. These type of sensors are deployed for serious patients because of the non-invasive monitoring, for instance physiological status of patients will be monitored by the IoT-driven sensors, which gathers physiological information regarding the patient through gateways and later analysed by the doctors and then stored in cloud, which enhances quality of healthcare and lessens the cost burden of the patient. The working principle of IoT in remote health monitoring systems is that it tracks the vital signs of the patient in real-time, and if the vital signs are abnormal, then it acts based on the problem in patient and notifies the doctor for further analysis. The IoT-driven sensor is attached to the patient and transmits the data regarding the vital signs from the patient's location by employing a telecom network with a transmitter to a hospital that has a remote monitoring system that reads the incoming data about the patient's vital signs.
A Novel Framework on Biomedical Image Analysis Based on Shape and Texture Classification for Complex Disease Diagnosis
Authors: A. Reyana , V. T. Krishnaprasath , J. Preethi
Published: July 2020

The wide acceptance of applying computer technology in medical imaging system for manipulation, display, and analysis contribute better improvement in achieving diagnostic confidence and accuracy on predicting diseases. Therefore, the need for biomedical image analysis to diagnose a particular type of disease or disorder by combining diverse images of human organs is a major challenge in most of the biomedical application systems. This chapter contributes an overview on the nature of biomedical images in electronic form facilitating computer processing and analysis of data. This describes the different types of images in the context of information gathering, screening, diagnosis, monitor, therapy, and control and evaluation. The characterization and digitization of the image content is important in the analysis and design of image transmission.
Deep Learning Techniques for Prediction, Detection, and Segmentation of Brain Tumors
Authors: Jayanthi Prisilla , Iyyanki Muralikrishna
Published: July 2020

In deep learning, the main techniques of neural networks, namely artificial neural network, convolutional neural network, recurrent neural network, and deep neural networks, are found to be very effective for medical data analyses. In this chapter, application of the techniques, viz., ANN, CNN, DNN, for detection of tumors in numerical and image data of brain tumor is presented. First, the case of ANN application is discussed for the prediction of the brain tumor for which the disease symptoms data in numerical form is the input. ANN modelling was implemented for classification of human ethnicity. Next the detection of the tumors from images is discussed for which CNN and DNN techniques are implemented. Other techniques discussed in this study are HSV color space, watershed segmentation and morphological operation, fuzzy entropy level set, which are used for segmenting tumor in brain tumor images. The FCN-8 and FCN-16 models are used to produce a semantic segmentation on the various images. In general terms, the techniques of deep learning detected the tumors by training image dataset.
Transforming Biomedical Applications Through Smart Sensing and Artificial Intelligence
Authors: T. J. Harini Akshaya , V. Suresh , M. Carmel Sobia
Published: July 2020

Electronic health records (EHR) have been adopted in many countries as they tend to play a major role in the healthcare systems. This is due to the fact that the high quality of data could be achieved at a very low cost. EHR is a platform where the data are stored digitally and the users could access and exchange data in a secured manner. The main objective of this chapter is to summarize recent development in wearable sensors integrated with the internet of things (IoT) system and their application to monitor patients with chronic disease and older people in their homes and community. The records are transmitted digitally through wireless communication devices through gateways and stored in the cloud computing environment.
Translating Internationalization Initiatives From the Macro to the Micro
Authors: Corrales Kathleen A. , Rey Paba Lourdes , Poole Paige Michael
Published: July 2020

Internationalization of higher education is a phenomenon affecting universities around the world in their effort to prepare students to interact in international and intercultural environments. This chapter presents a three-phased, professor-led, grassroots study aimed at, first, characterizing the state of internationalization at a particular Latin American university; second, defining what international and intercultural competences (IICs) should be adopted as the institutional goal for all students; and lastly, piloting pedagogical strategies and activities to bring the IICs into the classroom. Ultimately, this chapter hopes to serve as an example for how institutions can translate internationalization initiatives from the macro-level into the micro-level (the classroom) in a more inclusive way that better impacts student learning within the realm of internationalization at home. Likewise, this experience aims to help fill the current gap in the theory and practice of internationalization in Latin America.
Infusing Global Perspectives Into Teacher Education
Authors: López Minda Morren , Pu Chang
Published: July 2020

For decades, researchers and educators have called for the internationalization of teacher education and the infusion of global perspectives into preparation programs in order to better serve all children, regardless of citizenship, location, or status. This self-study of the authors' own processes and outcomes describes the transformation of two teacher preparation courses to include global competencies and content. Two key concepts, global competence and global competent teaching, were used to frame the redesigned courses. They aimed at helping candidates develop their own global competence and understand why global competence is an essential skill for their future students to acquire, as well as foster thinking routines and pedagogical practices to become global minded teachers and guide their students to build global competence. Although the university contexts and courses were different, results show commonalities and implications for educators working to internationalize courses in higher education.
Beyond Lead Generation
Authors: Morrison Joseph D.
Published: July 2020

International education is rooted in the ideals of diversity, inclusion, and cross-cultural understanding. However, the industry falls short of these ideals during the student recruitment process, which is often concentrated in just a few source markets, with impersonal systems and practices. New technology, notably artificial intelligence, is creating new opportunities for institutions to address this challenge. New platforms can spread the attention and engagement of university recruiters to every corner of the globe, deliver a more personalized experience to prospective applicants that have historically been ignored, improve campus diversity, and lessen the industry's climate impact by reducing the need for travel. Insights can be drawn from the high technology industry to create trust and scale, adequate venture capital is available globally, and organizations such as the Groningen Declaration Network (GDN) can provide the necessary governance. Together, these factors will enable a global electronic marketplace for education with greater diversity and personalization.
Serious Cooperative Board Games as an Innovative Approach in a Study Abroad Course in Peru
Authors: Bauserman Stewart , Jin Lan , Sheffield John W. , Mattingly Michael
Published: July 2020

The chapter describes how creating and playing a serious cooperative board game to address energy sustainability in a study abroad course provides an opportunity for students to collaborate in culturally diverse teams and develop intercultural competence. Learning leadership skills through the method of Agile Game Play, including team building, communication, and cooperative interaction for a global benefit, is shown to be effective. The serious cooperative board game can be seen as not merely an interactive support tool, but as a method to generate innovative, people-centered, approaches that can be applied to efforts in global energy sustainability and policy making. Creating and playing a serious cooperative board game offers a new approach for a student in any field of study to learn cooperative leadership skills for global benefit in a short amount of time.
Problematizing the Language of Internationalization in Higher Education
Authors: Malfatti Gabrielle , Villamil Astrid M.
Published: July 2020

Like most aspects of modern higher education, its internationalization is framed by terminology rooted in neoliberal practices. No aspect of academic life is more widely touched than internationalization, where encounters with the broad reach of capitalism and its legacy of inequalities are common place; and where the motivations, processes, and practices of individuals representing institutions of higher education have meaningful opportunities to reframe an increasingly transactional space. This chapter offers an analysis of commonly used terms and an invitation to delinking and re-imagining its vernacular.
The Creative Voice
Authors: Tupou Janet
Published: July 2020

This chapter analyses themes of hybrid diasporic Tongan identity in the individual talanoa shared by Tongan women that was captured in doctoral research, per the author. Special focus is put on issues of “individual freedom” and “the collective burden” of expressing voice in the “walk in two worlds” creatively and geographically between Tonga and New Zealand. Although the legal and cultural frameworks in Tonga are progressive and relatively liberal with regard to the promotion of gender equality, some laws and traditions discriminate against women, establishing gender inequalities. As this chapter demonstrates, these inequalities have had profound impacts on women and their agency. Tongan women have spearheaded efforts to bridge communal boundaries and challenge the increasing normalisation of male dominance by continuously expressing their voices, particularly through creativity. The following perspectives inform this exploration, which is deconstructed from the standpoint of a TIWI (Tongan Kiwi) woman.
Different Bioremediation Techniques for Management of Waste Water
Authors: Patra Biswajit , Deep Saroj Kumar , Pradhan Surya Narayan
Published: July 2020

Water contamination remains an issue. A combination of biodegradation and nanotechnology is proposed as a potential proficient, minimal effort, and naturally amiable system to deal with it. Among different mediations, bioremediation procedures can conceivably be utilized to decrease the versatility of materials in the subsurface, reducing the potential for human and ecological exposure. The metabolic diversity of microorganisms ensures an assortment of substrates to be expended. Photosynthetic microorganisms have been found as a compelling and eco-friendly species that can remove carbon, nitrogen, and phosphorous in the manufactured sewage and wastewater. This chapter particularly emphasizes environmentally friendly NMs that give information for removing contaminants from wastewater and effluents. Additionally, various nanocomposites and different natural methods utilized in the wastewater treatment process are also briefly discussed.
Forecasting the Crop Yield Production in Trichy District Using Fuzzy C-Means Algorithm and Multilayer Perceptron (MLP)
Authors: Geetha M. C. S.  , Shanthi I. Elizabeth
Published: July 2020

The agricultural stock depends upon several factors like biological, seasonal, and economic determinants. The growers sustain a vital loss if they are not capable of predicting the variations in these circumstances. The uncertainty on crop yield can be predicted in a logical and mathematical way. The forecast is made based on the previous archives of yield data secured from that area. Data mining is one such procedure practised to predict the crop yield. The systems examine the data, and on mining, several patterns based on numerous parameters predict the return. This article directs on crop yield forecast in Trichy district by adopting data mining techniques for rule formation on classifying the training data and implementing prediction for test data. The suggested method employs fuzzy C means algorithm for clustering and multilayer perceptron design for prediction. The results of accuracy and execution time of the proposed system correlated with the regression algorithm of prediction.
Food Waste Solutions in a Developing Country
Authors: Matzembacher Daniele Eckert , do Canto Natália Rohenkohl , Stangherlin Isadora do Carmo , Alves Ana Paula Ferreira , Dutra de Barcellos Marcia
Published: July 2020

The importance of integrating sustainability in businesses practices has gained increasing attention in the food sector. Important sustainable initiatives in this sector refer to food waste solutions. Food waste is defined as food intended to feed humans, but used in another way. This study aims to analyze food waste solutions developed by Brazilian companies. Through a multiple case study, three cases were analyzed. Results indicate that food waste solutions are incorporated mainly in collaboration and expansion, product, unit, and price-related categories. The study contributes by examining initiatives with different actors than retailers and within the context of a developing country, finding synergies and divergences with previous studies. In addition, new food waste solutions categories emerged and complement the analysis.
Do Star Ratings Matter?
Authors: Joshi Gauri , Sen Vasundhara , Kunte Monica
Published: July 2020

Increasing environmental concerns have resulted in consumers indulging in conserving energy by curtailing energy usage rather than switching to energy efficient practices. Energy efficient appliances (EEAs) offer the dual advantages of appliance usage with reduced energy consumption. Research suggests that use of such appliances, in residences is limited. This study was thus undertaken to understand individual resident's awareness towards EEAs and factors influencing their purchase. A qualitative approach consisting of 31 personal interviews were conducted with individuals from socio-economic categories A1, A2 and B1. While awareness of EEAs was present among respondents; benefits of using such appliances were neither widely known nor easily quantifiable. Purchase decisions were ruled by appliance price but did not deter adoption, the availability of appliances in desired aesthetics and family involvement in purchase decision. Higher penetration of such appliances can be ensured if consumers can estimate exact savings in monthly electricity bills due to EEAs at the time of purchase.
An Enhanced Computational Fusion Technique for Security of Authentication of Electronic Voting System
Authors: Adewale Olumide Sunday  , Olutayo Boyinbode , Adekunle Salako E.
Published: July 2020

The detection of a false individual who had not been enrolled as a genuine participant in an election could be potentially detected in electronic voting systems as against paper-based methods. In recent time, one-time password and biometrics have been used to curtail false acceptance of imposters. However, imposters had unlawfully stolen the credentials of genuine individuals, gained unauthorized access, and polled illegitimate votes due to poor authentication methodology. The accuracy of a multi-biometric system is a function of the data type used and fusion method adopted. This paper presented a computational fusion approach that involved the use of fingerprint and randomly generated voter identification number to effectively satisfy the authentication security requirement of the electronic voting system. New architectural and mathematical equations on the proposed approach were presented to tackle the problem of false acceptance rate and improve on the true acceptance rate of a biometric system. Algorithm to achieve the proposed approach was presented in this paper as well.
Distributed Quantiles Estimation of Sensor Network Measurements
Authors: Lee Jongmin , Tepedelenlioglu Cihan , Spanias Andreas , Muniraju Gowtham
Published: July 2020

A quantile is a value below which random draws from a distribution falls with a given probability. In a centralized setting where the cumulative distribution function (CDF) is unknown, empirical CDF can be used to estimate quantiles after data aggregation. In a distributed sensor network, it is challenging to estimate quantiles, as each sensor observes local measurement data with limited storage and transmission power, which makes it difficult to obtain the global ECDF. This paper proposes consensus-based quantile estimation for such networks, even when communication links are corrupted by independent random noise. The state-values are recursively updated with two steps: a local update based on measurement data and current state and averaging updated states with local nodes. The estimated state sequence is shown to be asymptotically unbiased and converges toward the sample quantile in the mean-square sense. Applications on the distributed estimation of trimmed mean; computation of median, maximum, or minimum values; and identification of outliers through simulation are also provided.
An Innovative Modelling and Decision-Support Approach for Evaluating Urban Transshipment Problems Using Electrical Trucks
Authors: Gunalay Yavuz , Yeomans Julian Scott
Published: July 2020

As a consequence of urban intensification, logistics planning becomes more important than ever. Electric vehicles have proved to be both environmentally friendly and a lower-cost alternative to internal combustion engine vehicles. However, existing decision methods employed by businesses and municipalities are not universally conducive to the optimization and evaluation of urban transportation systems. An innovative model and planning approach is proposed to enable urban planners to more readily evaluate the contribution of electric vehicles in city logistics and to support the decision-making process. When faced with decision-making situations that involve multiple and inconsistent performance objectives, it is often preferable to consider several quantifiably good alternatives that provide various, very different perspectives. This paper provides a modeling-to-generate-alternatives (MGA) decision-support procedure that uses the firefly algorithm (FA) metaheuristic for generating sets of maximally different alternatives for electric vehicle planning in urban transshipment problems.
Parametric Analysis and Design of 28GHz Microstrip Patch Antenna
Authors: Saxena Raghuraj Sharan , Shrivastava Rishik , Muchhal Ritu , Tiwari Rahul
Published: July 2020

As the wireless technology is advancing rapidly, there is also an increasing demand for high data rates and large bandwidth. So, the new generation technology (5G) is proposed. For this purpose, there is a need of advanced antenna design, and here the authors are using a microstrip patch antenna, which is highly preferred due to low profile, simple manufacturing, and ease of feeding. This research presents the design of 28.132 GHz microstrip patch antenna. We have used FR-4 substrate here is which has a dielectric constant Er= 4.3 and a thickness of 0.5 mm. The dimensions of patch are 4.8×6.8×0.5mm including the ground plane. It has a bandwidth of 1.613 GHz, return loss of -19.175 dB, VSWR 1.24 dB, VSWR as 1.24 dB, gain as 3.82 dB and total efficiency of -3.116 dB.. The designing and simulation of this antenna is performed by CST studio suite software and various specifications such as S-parameter, VSWR, and radiation pattern is discussed. Furthermore, comparative analysis is done, which is indicating the variation of antenna parameters on varying the design dimensions.
Modelling of Logistics Monitoring System for Milk Collection Based on Swarm Intelligence
Authors: Elgarej Mouhcine , Mansouri Khalifa , Youssfi Mohamed
Published: July 2020

Over the last 30 years, the milk processing process has shifted from the farm to the centralized cheese factory, which has had an impact on the management of transport logistics. In Morocco, several dairy units are located in rural areas with a poor road network, which means that milk collection has a significant impact on profit, affecting milk transport costs. The objective of this work is to develop a decision support tool based on internet of things technologies to optimize milk collection routes, reduce the cost of milk transport, and improve collection density. The tool developed in this study is based on a SIG system and farm milk volumes to estimate the cost per liter of milk for the regular route and to recalculate the same cost for the optimized collection route, combined with IoT technology to ensure the communication process between dairy farms, trucks, and dairy plants.
Pain in child patients: A review on managements
Authors: Dezfouli Seyedeh Mahsa Mahmoudinezhad , Khosravi Shaqayeq
Published: July 2020

Pain has been known as one of the major universal health concerns about ill children, because of its morbidity and potential mortality. Pain suitable evaluation is a challenge in children because the verbalization is difficult. Low clinical information, few pediatric researches, and the worry of opioid side effects make difficult to provide satisfactory treatments. Many pharmacologic and non-pharmacologic strategies to manage pain exist for pediatric pain treatment. The purpose of this review article is to describe exhaustively pain mechanism, evaluation and management by review literature from January 2000 to January 2019 using PubMed, EMBASE, MEDLINE, LILACS databases. Pharmacological and integrative non-pharmacological therapies has been indicated in acute and chronic pain treatment. Opioids and opioid-sparing agents target nociceptive and neuropathic pain. With due attention to available results, an early combination of pharmacological and integrative non pharmacological treatments are indicated in children pain management.
Muscle function impairment in cancer patients in pre-cachexia stage
Authors: Dalise Stefania , Tropea Peppino , Galli Luca , Sbrana Andrea , Chisari Carmelo
Published: July 2020

Cancer cachexia has been reported to be directly responsible for at least 20% of cancer deaths. Management of muscle wasting in cancer-associated cachexia appears to be of pivotal importance for survival of patients. In this regard, it would be interesting to identify before its patent appearance eventual functional markers of muscle damage, to plan specific exercise protocols to counteract cachexia. The muscle function of 13 oncologic patients and 15 controls was analyzed through: i) analysis of the oxidative metabolism, indirectly evaluated trough dosage of blood lactate levels before and after a submaximal incremental exercise on a treadmill; ii) analysis of strength and, iii) endurance, in both lower and upper limbs muscles, employing an isokinetic dynamometer. Statistical analyses were carried out to compare the muscle activities between groups. Analysis of oxidative metabolism during the incremental exercise on a treadmill showed that patients performed a shorter exercise than controls. Lactate levels were significantly higher in patients both at baseline and after the task. Muscle strength analysis in patients group showed a reduction of Maximum Voluntary Contraction during the isometric contraction and, a tendency to fatigue during endurance task. Data emerging from this study highlight an impairment of muscle oxidative metabolism in subjects affected by a pre-cachexia stage of cancer. A trend of precocious fatigability and an impairment of muscle strength production were also observed. This evidence underlines the relevance of assessing muscle function in order to develop novel rehabilitative approaches able to counteract motor impairment and eventually to prevent cachexia in these patients.
Development and evaluation of sago (Metroxylon sagu) pith extractor
Authors: Bagasbas Jefrey M. , Barroca Renyl B.
Published: July 2020

Among the significant problems in the sago processing, the extraction of the starch from its trunk tops the list. The extraction process involves a debarking and rasping process that is very tedious, unsanitary and time consuming that dramatically affects the quality of starch production since the local processor relies mainly on conventional method of extraction. This paper presents the design, fabrication and performance evaluation of sago pith extraction machine. The design concept made was to rasp the sago pith using a rotating rasper without debarking the log to minimize the steps on the extraction process. Four different teeth spacing of the rasper were considered during the testing and replicated three times; 1 cm, 2 cm, 3 cm, and no teeth as controlled parameters, respectively. Results revealed that teeth spacing has a significant effect on the performance of the machine such as extraction capacity, extraction efficiency and fineness of rasped pith. Based on average, the highest extraction capacity was recorded at 217.47 kg/h using 3 cm teeth spacing, and the highest extraction efficiency was 96.12% using 2 cm teeth spacing and the finest rasped pith having the lowest fineness modulus of 2.15 was when 1 cm teeth spacing is used. Compared to manual and other existing mechanical rasper accounting the process of debarking, machine’s extraction capacity is higher, more efficient, safer and hygienic. Cost and benefit analysis supports that the machine is profitable and the financial efficiency is high having a 65% rate of return and 1.8 years payback period.
L’argomentazione medico-paziente: il problema della comunicazione dal punto di vista retorico e bioetico
Authors: Caporale Cinzia , Zagarella Roberta Martina
Published: July 2020

Nell’epoca del post-paternalismo medico, la comunicazione medico-paziente è divenuta oggetto di studio in ambiti disciplinari molto diversi tra loro. In generale, però, tali ricerche sottendono una visione del linguaggio che presenta alcuni problemi sia da un punto di vista teorico sia bioetico. A partire da tale considerazione preliminare, il testo propone, in una prima parte, di analizzare l’interazione discorsiva medico-paziente nel contesto degli studi di filosofia del linguaggio, discutendo in particolare tre false credenze diffuse sulla comunicazione (linguaggio come strumento; modello postale della comunicazione; pregiudizio nei confronti della persuasione). Sgombrato il campo dai pregiudizi sul linguaggio, nella seconda parte il testo mette a confronto due diversi modelli dell’argomentazione (pragma-dialettica e retorica), sostenendo la particolare fecondità dell’intreccio tra retorica e bioetica nella descrizione dell’interazione discorsiva medico-paziente.
Human embryo: what about relatedness?
Authors: Terranova Corrado , Angioli Roberto , Feole Laura , Plotti Francesco , Fais Giuseppina , Rampello Stefania , Campanozzi Laura , Ricci Giovanna , Ghilardi Giampaolo , Tambone Vittoradolfo
Published: July 2020

Many studies are still ongoing to allow a global comprehension of the complex mechanisms that characterize and regulate human embryo development during the first weeks of his life. In this article, we decided to explore in particular one aspect of human embryo development: relatedness. Using PubMed database, we selected articles related to this particular theme and 56 articles where included in our analysis. We considered three different types of relatedness: from embryo to mother, from mother to embryo and bilateral relatedness. For each article, we indicated what type of relatedness was mainly present either during pre-implantation phase or during implantation phase or during post-implantation phase. The complex interactions between the mother and the embryo have been discussed and represented using, as emerged from literature, a cooperative agents’ model.
A case of lung injury resembling diffuse pulmonary hemorrhage after the first administration of alemtuzumab in a patient with multiple sclerosis. Role of the HRCT
Authors: Cipolla Gaia , Relo Rosalba , Pasciuta Elisa , Catalano Domenica , Lo Bello Federica , Coppolino Irene , Ruggeri Paolo , Proietto Alfio , Buccafusca Maria , Cutroneo Paola Maria , Trifirò Gianluca , Caramori Gaetano
Published: July 2020

Diffuse alveolar hemorrhage (DAH) is an acute often life-threatening condition characterized by a variable combination of hemoptysis, dyspnoea, diffuse and bilateral ground glass pulmonary opacities, anemia and hypoxemia, that can be induced by different causes, including several drugs. We report here the case of a 25-year-old woman who has been admitted to our pulmonary clinic for the onset of chest pain, cough and haemoptysis, started one week after her first treatment with alemtuzumab for multiple sclerosis. Computed tomography (CT) scan of the chest at the admission showed diffuse and bilateral ground glass pulmonary opacities. Her symptoms resolved completely without any treatment, after the interruption of alemtuzumab, and CT scan of the chest performed one month later showed total disappearance of the pulmonary opacities.
Effects of mannuronic acid (M2000) on gene expression profile of signal transducer and activator of transcription proteins (STATs) in rheumatoid arthritis patients
Authors: Gaafar N.A.G. , Aslani M. , Aghazadeh Z. , Mortazavi-Jahromi S.S. , Razavi A. , Mirshafiey A.
Published: July 2020

Rheumatoid arthritis (RA), a form of inflammatory arthritis, is a chronic joint disease characterized by pain and inflammation that affects 0.5% to 1% of the population worldwide. The safety, efficacy, tolerability, and potency of β-D-mannuronic acid (M2000) as a novel NSAID with immunosuppressive property has been reported by several in vitro studies, experimental models and clinical trials phase I/II and III in ankylosing spondylitis and rheumatoid arthritis (RA) patients This research is designed to study the therapeutic efficacy of oral administration of mannuronic acid in RA patients who had inadequate response to conventional drugs and to assess the effect of this drug on gene expression of the signal transducer and activator of transcription (STATs) protein (STAT1, STAT3, STAT4, and STAT6). The study has included 15 RA patients who had an insufficient response to the conventional therapy. The oral dose of mannuronic acid was 1000mg divided into two 500 mg doses per day for 3 months as an addition to conventional therapy. There were 15 healthy volunteer in the control group. Blood samples were collected from both groups, once from healthy controls and twice from RA patients before and after treatment by M2000. The peripheral blood mononuclear cells (PBMCs) were isolated to assess the gene expression level of STAT1, STAT3, STAT4, and STAT6 using the real-time PCR method. Results obtained in this study demonstrated a significant difference in the gene expression level of STAT1 between healthy controls and patients before treatment as well as a significant reduction in RA patients after treatment compared with the level before treatment. In addition, the gene expression level of STAT3 and STAT4 showed a significant reduction in RA patients after treatment compared to patients before treatment, while there was no significant difference between RA patients before treatment and the healthy control group for both molecules. On the other hand, there was no change in the gene expression level of STAT6 among all groups. The outcomes of this study confirmed that β-D-mannuronic acid (M2000) has the ability to control the levels of STAT1, STAT3 and STAT4 in RA patients, and might be beneficial in the management and therapy of RA.