bluuebunny/crossref_metadata_2025 huggingface dataset:
Food Safety and Climate Change
Authors: Zinedine Abdellah , El Akhdari Samira
Published: January 2019

Mycotoxins are chemical compounds produced mainly by mounds of genera Aspergillus, Penicillium, and Fusarium on various grains and agricultural commodities at different stages in the field, before harvest, post-harvest, during processing, packaging, distribution, and storage. The production of mycotoxins depends on several environmental factors such as temperature and moisture. This chapter gives an overview about the major mycotoxins (e.g., aflatoxins, ochratoxin A, and Fusarium toxins), masked mycotoxins, and emerging mycotoxins. The toxicity of these mycotoxins and their negative economic impact was also discussed together with the effect of climate change on their production. A section on mycotoxins regulations by international agencies and organisms (WHO, FAO, EU, etc.) was discussed. Finally, the different strategies to reduce or eliminate the toxic effects of mycotoxins in contaminated foods and feeds by using chemical, physical, and biological/biotechnological methods or innovative approaches were explained.
Climate Change Outcomes on the Environmental Ecotoxicology
Authors: El Baz Soraia
Published: January 2019

Climate change is a daunting problem and has only recently attracted attention. This chapter presents a review on the implications of climate change on the regulation, and modelling of toxic pollutants. Also, it identifies relationships between climate fluctuations and changes in some polluants distribution (heavy metals, hydrocarbons, and pesticides). Moreover, the influence of climate change on polluant environmental behavior is explored by studying polluants response to inter-annual climate fluctuations such as precipitation and temperature. Therefore, it will be important to monitor strategies taking into account climate change and new regulatory plans should be devised in toxics polluant management.
Climatic Factors Impacting Leishmaniasis Risk in a Global View
Authors: Kahime Kholoud , El Hidan Moulay Abdelmonaim , Sereno Denis , Lahouari Bounoua , Ben Salem Abdelkrim , Mansour Abdellaziz Ait , Messouli Mohammed , Khebiza Mohammed Yacoubi
Published: January 2019

Leishmaniasis is a complex disease comprised of multiple organisms in association. Each of these organisms responds differently to external factors. The environmental and socio-economic associations contribute to the dynamics and emergence of leishmaniasis across the globe. Ecological dynamics of the vector-parasite-host system of leishmaniasis influenced directly and indirectly both human and animal health. The transitions and rapid climate and socio-economic changes caused a transition of emergence and re-emergence of leishmaniasis outbreaks. The pattern of changes is influenced by the distribution and abundance as well as the spatial dynamics of vector and reservoirs species, which in turn disrupts ecosystem structure of vector and parasite. In Morocco, leishmaniasis are endemic and constitute a major public health threat. The observations showed significant variations in its spatial distribution and forms through Morocco with increase in the number of recorded cases during the last couple of years. Here, the authors discuss disease change related to climate and socio-economic influence.
Climate Change and Fecal Peril
Authors: Khadra Ahmed
Published: January 2019

Fecal peril caused by intestinal parasites is commonly reported to be causing health problems in the world. Furthermore, global climate change is inevitable. The purpose of this chapter is to examine the health effects of climate change. Water shortage contribute to increase the pressure on regional water resources and force a greater number of people to use urban wastewater as an alternative for irrigation. Therefore, unsafe management and inappropriate wastewater use in urban agriculture is likely to be responsible of exacerbating the transmission of infectious diseases, including those caused by intestinal protozoa and helminths parasitic worms. It should be taken into account that waterborne diseases are influencedby climate change. The frequency and severity of intertwined extreme weather events driven by climate change are occurring worldwide and likely to cause epidemics of waterborne gastroenteritis. The association found between both rainfall, river flooding, and the majority of waterborne disease outbreaks was frequently proved to be preceded by climatic change events.
Climate Change Effects on Venomous Snakes
Authors: Bouazza Abdellah , El Hidan Moulay Abdelmonaim , Aimrane Abdelmohcine , Kahime Kholoud , Lansari Aziza , Laaradia Mehdi Ait , Lahouaoui Hasna , Moukrim Abdellatif
Published: January 2019

The purpose of this chapter is to examine the evidence of a relationship between climatic changes and snake species distribution in relation with the snakebites risk increment against human populations. The global climatic change is a key factor leading to snake species behavioral changes mainly because of the rise of temperature. The variety of venomous snakes and their related potency toward human being have been well documented. Thus, this may serve as a basic knowledge for any preventive act in the face of snake toxins and their caused physiopathological and clinical effects. In addition, several studies have shown that global warming have caused a change in snake habitat and distribution, thus leading to an increase of overlapped human and snake populations living territories which raise up the risk of envenomation. Globally, more than 20,000 deaths occur every year with a high tendency to increase. Thus, consideration of human risk of envenomation may be fundamental to the effective intervention in epidemiological and clinical scales.
Developing an Effective Classification Model for Medical Data Analysis
Authors: Mahoto Naeem Ahmed , Babar Abdul Hafeez
Published: January 2019

The sparse nature of medical data makes knowledge discovery and prediction a complex task for analysis. Machine learning algorithms have produced promising results for diversified data. This chapter constructs the effective classification model for medical data analysis. In particular, nine classification models, namely Naïve Bayes, decision tree (i.e., J48 and Random Forest), multilayer perceptron, radial bias function, k-nearest neighbors, single conjunctive rule learner, support vector machine, and simple logistics have been applied for developing an effective model. Besides, classification models have also been used in conjunction with ensemble learning methods, since ensemble methods significantly increase the predictive outcomes of the classification models. The evaluation of classification models has been measured using accuracy, f-measure, precision, and recall metrics. The empirical results revealed that the combination of ensemble learning methods with classification models produces better predictions in comparison with sole classification model for the medical data.
Synthesis of Classification Models and Review in the Field of Machine Learning
Authors: Kari Venkatram , Amalanathan Geetha Mary
Published: January 2019

Classification method is an important technique used in machine learning for predictive analytics. Classification enables business to predict future trends and behaviors of an enterprise with the help of their past data. Classification is a supervised learning model, which is built in twostep process, first building the classification model and second predicting the outcome for unknown data. This chapter describes various classification models by learning mechanisms and categorizes them into different statistical, probabilistic, and heuristic methods, and explains them with example dataset. It also compares these models and their efficiencies with model evaluation techniques and briefs some blended classification models. The goal of this chapter is to provide a comprehensive review of different classification techniques and give a quick refresher on classification models in big data analytics. The comparison of various classification models helps the readers to quickly decide which classification model to choose for the given business scenario.
Arrhythmia ECG Beats Classification Using Wavelet-Based Features and Support Vector Machine Classifier
Authors: Jha Chandan Kumar , Kolekar Maheshkumar H.
Published: January 2019

Abnormal behavior of heart muscles generates irregular heartbeats which are collectively known as arrhythmia. Classification of arrhythmia beats plays a prominent role in electrocardiogram (ECG) analysis. It is widely used in online and long-term patient monitoring systems. This chapter reports a classification technique to recognize normal (N) and five arrhythmia beats (i.e., left bundle branch block [LBBB], right bundle branch block [RBBB], premature ventricular contraction [V], paced [P], and atrial premature contraction [A]). The technique utilizes features of heartbeats extracted by the wavelet multi-resolution analysis. The feature vectors are used to train and test the classifier based on the support vector machine which has been emerged as a benchmark in machine learning classifier. It accomplishes the beat classification very efficiently. ECG records of the MIT-BIH arrhythmia database are utilized to acquire the different types of heartbeats. Performance of the proposed classifier outperforms the contemporary arrhythmia beats classification techniques.
Real-Time Cardio Monitoring and Characterization of Diseases Introducing Statistical and Spectrogram Analysis
Authors: Bhattacharjee Soumyendu , Ghosh Subham , Neogi Biswarup
Published: January 2019

This chapter provides significant theoretical and systematic frameworks and the latest empirical research towards the development of an automated cardiovascular disorder diagnostic system with the classifier. This research proposes an accurate non-invasive model of the cardiovascular diseases diagnostic system. This model of diagnostic system support superior mobility with continuous real-time monitoring facility. This monitoring system will uncover a new dimension towards cardiovascular research. A physician will able to monitor several heart patients remotely with this device. Also, they can prescribe proper medicine remotely to the patient in an emergency. The system also has a provision to alert the patient by predicting the specific type of cardiovascular disorder accurately. An automated cardiovascular disorder diagnostic system development focuses towards the prime objective. Another objective is the adoption of modern classification technique for detecting cardiovascular disorders with high accuracy.
Hybrid Multimodality Medical Image Fusion Using Various Fusion Techniques With Quantitative and Qualitative Analysis
Authors: Rajalingam B.  , Priya R.  , Bhavani R.
Published: January 2019

In this chapter, different types of image fusion techniques have been studied and evaluated in the medical applications. The ultimate goal of this proposed method is to obtain the fused image without any loss of similar information and preserve all special features present in the input medical images. This method is used to improve the fused image quality for better diagnosis of critical disease analysis. The fused hybrid multimodal medical image should convey better visual description than the individual input images. This chapter proposes the method for multimodal medical image fusion using the hybrid fusion algorithm. The computed tomography, magnetic resonance imaging, positron emission tomography, and single photon emission computed tomography are the input images used for this experimental work. In this chapter, experimental results discovered that the proposed techniques provide better visualization of fused image and gives the superior results compared to various existing traditional algorithms.
Cultivating Visual Analysis and Critical Thinking Skills Through Experiential Art
Authors: Page Morgan C.
Published: January 2019

Employing visual analysis in the production and critique of artwork is an essential task of an art educator. By encouraging the basic principles of Edmund Burke Feldman's Practical Art Criticism in the development of art making and art analysis, art educators can create a learning environment that guides students toward the practice of higher order thinking skills. Examples of immersive art education that activates space and invites participation from the viewer will be cited as systems for inspiring civic engagement in the classroom.
Smart Ads for Better User Targeting
Authors: Asmaryan Albert , Levanov Alexey , Borovik Irina
Published: January 2019

Currently, there is a problem of contextual advertising. Advertisers want to be able to clearly target the audience because user experience and revenue depend on the relevance of the displayed ads. Today's technology makes it easier not only to collect a wealth of information but also to ensure that it accurately reflects on your target audience, industry, and ad campaigns. Contextual advertising supports much of the web's ecosystem today online but not offline. The task was to develop a system prototype and scale it, which gives the ability to display advertising based on user interests in real life based on the best techniques of contextual advertising.
Energy-Efficient Design of LTE Systems
Authors: Dixit Saurabh , Katiyar Himanshu , Singh Arun Kumar
Published: January 2019

There has been a paradigm shift in the field of mobile communication, with an overwhelming increase in data usage. As more and more users are migrating to smartphones, the amount of data being transmitted has increased. However, huge amounts of data and signal propagation are bound to be detrimental to the ecological balance. Long-term evolution (LTE), due to its flexibility and backward compatibility, has emerged as the network of choice for 4G and beyond. In this chapter, the significance of core technologies for LTE network is highlighted, along with the inherent advantage of reducing the energy consumption of cellular network. An energy-efficient design of LTE is proposed that blends the technologies proposed by 3GPP such as adaptive OFDMA with that of MU-MIMO.
Multidimensional Analysis of LTE Network Rollout With Typical and Non-Typical Antenna Configurations
Authors: Sheikh Muhammad Usman , Lempiainen Jukka , Jantti Riku
Published: January 2019

Higher order sectorization and the site densification are the two renowned solutions for the cellular system capacity crunch. However, in order to take adequate benefits of these techniques they should be implemented with optimal antenna configuration. This chapter highlights the gain of using an optimized antenna configuration for three- and six-sector sites in achieving a better network coverage and network quality (i.e., capacity). Unlike traditional wide 65° HPBW antenna, this chapter also focuses on the use of other narrow HPBW antennas for three- and six-sector sites. This chapter provides detailed analysis of network performance from coverage, capacity, spectral-efficiency, power-efficiency, and cost-efficiency point of view. It also provides a fair comparison between the network rollout with traditional three-sector sites and higher order six-sector sites. Similarly, the impact of site densification along with sector densification is also studied in this chapter.
Digital Communications and a Smart World
Authors: Zhong Hua
Published: January 2019

This chapter is devoted to digital communications in a smart world. The author examines turbo codes that are currently introduced in many international standards and implemented in numerous advanced communication systems, applied in a smart world, and evaluate the process of extrinsic information transfer (EXIT). The convergence properties of the iterative decoding process, associated with a given turbo-coding scheme, are estimated using the analysis technique based on so-called EXIT charts. This approach provides a possibility to predict the bit-error rate (BER) of a turbo code system with only the extrinsic information transfer chart. The idea is to consider the associated soft-input soft-output (SISO) stages as information processors, which map input a priori log likelihood ratios (LLRs) onto output extrinsic LLRs. Compared with other methods, the suggested approach provides insight into the iterative behavior of linear turbo systems with substantial reduction in numerical complexity.
Hyperspectral Microwave Atmospheric Sounder (HyMAS) Graphical User Interface Design
Authors: Javidi Giti
Published: January 2019

The hyperspectral microwave atmospheric sounder (HyMAS), for weather and climate missions, is capable of all-weather sounding equivalent to hyperspectral infrared sounders (in which clouds decrease the accuracy of the results) in clear air with vertical resolution of approximately 1 km. This will improve both the vertical and horizontal resolutions of the atmosphere. Through the use of independent RF antennas that sample the volume of the Earth's atmosphere through various levels of frequencies, thereby producing a set of dense, spaced vertical weighting functions, hyperspectral microwave is achieved. This yields surface precipitation rate and water path retrievals for small hail, soft hail, or snow pellets, snow, rainwater, etc. with high accuracies. One of HyMAS requirements is a graphical user interface (GUI). Hyperspectral measurements allow the user to determine the Earth's temperature with vertical resolution exceeding 1km (1093.61 yards).
Simulation of a Frequency-Modulated Continuous-Wave (FMCW) Radar Using Fast Fourier Transforms (FFT)
Authors: Eslami Akbar
Published: January 2019

Frequency-modulated continuous-wave (FMCW) radar systems send known frequency signals to moving targets and receive the signal back to detectors. FMCW systems can be used to measure exact heights of landing aircrafts. In addition, they are used in early warning radar systems and in proximity sensors. The advantage of using these radar signals is that the object target velocity and range can be quickly calculated using fast Fourier transforms (FFT). Taking the row-wise FFT of the signal matrix gives range information in form of range bins. Then taking column-wise FFT enables displaying the velocity for each range bin. The three-dimensional graph of the resulting matrix gives a signal power plot with respect to both the range bin numbers and their velocity.
Real-Time Digital Signal Processing-Based Algorithm for Universal Software Radio Peripheral to Detect GPS Signal
Authors: Sheybani Ehsan
Published: January 2019

Software-defined radios (SDR) are gradually becoming a practical option for implementing RF communication systems due to their low cost, off-the-shelf availability, and flexibility. Although the analog limitations of the hardware devices in these systems create barriers to some applications, creative algorithms in digital signal processing (DSP) can improve the results. In some cases, this improvement is essential to establishing a robust and reliable communication. The universal software radio peripheral (USRP) is a popular hardware that can be used alongside the SDR. Among many capabilities of USRP and its changeable daughter boards is receiving GPS signals. The GPS satellites transmit data on two main frequencies, L1 (1575.42 MHz) and L2 (1227.60 MHz). In this chapter, the focus is on describing a detailed implementation of the real-time DSP-based algorithm for USRP to detect GPS signal, namely the L1 band that transmits at 1575.42 MHz.
An Indian and Global Perspective on Cybercrime
Authors: Umadevi K. S. , Amali Geraldine Bessie , Subramanian Latha
Published: January 2019

Cybercrime is defined as a crime in which a computer is the object of the crime (hacking, phishing, spamming) or is used as a tool to commit an offense (child pornography, hate crimes). The advancement of technology has made us dependent on internet for all our needs. Internet has given us easy access to everything without moving from our place. Social networking, online shopping, storing data, gaming, online studying, online jobs, every possible thing that man can think of can be done through the medium of internet. However, with the development of the internet and its related benefits, the concept of cybercrimes arose. Cybercrimes are committed in different forms. In a report published by the National Crime Records Bureau, the incidence of cybercrimes under the IT Act has increased by 85.4% in the year 2011 as compared to 2010 in India, whereas the increase in incidence of the crime under IPC is by 18.5% as compared to the year 2010.
Smart Video Surveillance Systems and Identification of Human Behavior Analysis
Authors: Sivabalakrishnan M. , Menaka R. , Jeeva S.
Published: January 2019

Smart surveillance cameras are placed in many places such as bank, hospital, toll gates, airports, etc. To take advantage of the video in real time, a human must monitor the system continuously in order to alert security officers if there is an emergency. Besides, for event detection a person can observe four cameras with good accuracy at a time. Therefore, this requires expensive human resources for real-time video surveillance using current technology. The framework of ATM video surveillance system encompassing various factors, such as image acquisition, background estimation, background subtraction, store, and further process like segmentation, people counting, and tracking are done in cloud environment briefly discussed in this chapter.
Intelligent Malware Detection Using Deep Dilated Residual Networks for Cyber Security
Authors: Roseline S. Abijah , Geetha S.
Published: January 2019

Malware is the most serious security threat, which possibly targets billions of devices like personal computers, smartphones, etc. across the world. Malware classification and detection is a challenging task due to the targeted, zero-day, and stealthy nature of advanced and new malwares. The traditional signature detection methods like antivirus software were effective for detecting known malwares. At present, there are various solutions for detection of such unknown malwares employing feature-based machine learning algorithms. Machine learning techniques detect known malwares effectively but are not optimal and show a low accuracy rate for unknown malwares. This chapter explores a novel deep learning model called deep dilated residual network model for malware image classification. The proposed model showed a higher accuracy of 98.50% and 99.14% on Kaggle Malimg and BIG 2015 datasets, respectively. The new malwares can be handled in real-time with minimal human interaction using the proposed deep residual model.
Secured Information Exchange Using Haptic Codes
Authors: Kanna B. Rajesh
Published: January 2019

This chapter discloses an invention related to methods and systems to provide secure and custom information exchange code for the users of haptic or kinesthetic communication devices in a variety of applications. The proposed information exchange codes are named as “haptic codes,” where it maps several touch interactive locations into a single information exchange code. Thus, the proposed haptic code facilitates the representation of different notions to unique information exchange character/digit/symbol. A method has been invented to design eight such codes from the intuitive touch gestures (ITG) of user, each of which uses double-touch on arbitrary location within the touch pad/screen without shifting hand position on every touch. Hand position may or may not be the same after the generation of every ITG. Haptic codes are made secure by incorporating a new cryptographic system, which employs polar graph for encoding and decoding such locations using polar curves as shareable keys. Therefore, haptic codes can be exchanged for secure communication and read by devices that supports to touch.
Real-Time ECG-Based Biometric Authentication System
Authors: Mohan Jagannath , Kanagasabai Adalarasu , Pandu Vetrivelan
Published: January 2019

Security plays an important role in present day situation where identity fraud and terrorism pose a great threat. Recognizing human using computers or any artificial systems not only affords some efficient security outcomes but also facilitates human services, especially in the zone of conflict. In the recent decade, the demand for improvement in security for personal data storage has grown rapidly, and among the potential alternatives, it is one that employs innovative biometric identification techniques. Amongst these behavioral biometric techniques, the electrocardiogram (ECG) is being chosen as a physiological modality due to the uniqueness of its characteristics which integrates liveness detection, significantly preventing spoof attacks. The chapter discusses the overview of existing preprocessing, feature extraction, and classification methods for ECG-based biometric authentication. The proposed system is intended to develop applications for real-time authentication.
Using Multimodal Narratives in Professional Development to Support Collaborative Work
Authors: Lopes J. Bernardino
Published: January 2019

In this chapter, the authors discuss professional development (PD), self- and hetero-directed based on cases of physics education teachers in secondary and higher education and the role that multimodal narratives have in both processes. They adopt the PD perspective, which assumes that PD should be evaluated by its impact on teaching practices improvement. In this context, the PD aims to improve, incrementally, teaching practices. This process is difficult and complex and involves both teachers themselves and other professionals. Multimodal narratives (MN) are a tool that makes it possible to make teaching practices public and thus open to analysis by the teacher, other professionals, and researchers. The reported PD uses MNs as a tool that supports the teacher's collaborative work with peers and researchers. This collaborative work results in important incremental improvements in teaching practices.
Accessing Science Museum Educators' Discourse Through Multimodal Narratives
Authors: Afonso Susana , Afonso Ana Sofia
Published: January 2019

Museum educators play an important role in science communication, as they connect elements of an exhibit with visitors through emotion-driven experiences that are meaningful to them. Language is their main modus operandi in face-to-face interactions, but little is known of how they use it to communicate science, in part because little attention has been given to their practices and professional development. Nowadays, museums are changing, and science communication has become more demanding as these institutions exhibit hot themes of science. In this context, it is important that museum educators become aware of how they communicate science with an intended audience and reflect on how their practice can be improved. In this chapter, the authors focus on the way multimodal narratives can be used as a tool to access museum educators' discourse as well as how to promote museum educators' reflection about their practice and their professional development.
Multimodal Narratives in Nursing Education
Authors: Rua Marília , Leal Rita M. F. , Costa Nilza
Published: January 2019

Nursing education is driven by emerging challenges of scientific, technological, and professional advances that require the use of strategies that promote students' development of critical thinking for decision making in different contexts. It also requires that teachers constantly reflect on their pedagogical practices and (re)think them using strategies that allow their enhancement. The use of multimodal narratives (MNs) can be an important tool for teachers' professional development, namely to improve their classroom practices. Given the novelty of the use of MNs in nursing education, this chapter presents an analysis concerning the experience of making a MN and how it has been reflected in the authors' pedagogical practices. With this experience, potentialities of continuing to use MNs in nurse education are explored.
Understanding Motivation Factors in Green IT Adoption
Authors: Hernandez Alexander A.
Published: January 2019

Green information technology entails the resource-efficient consumption through the use of IT infrastructure to ensure sustainable business and environmental performance. This article explores the perceptions of firms who have adopted Green IT, by developing a conceptual framework that reflects the motivation factors in Green IT adoption in developing countries. The framework was tested using a structured survey and deployed to senior managers of manufacturing and service industries. Results indicated that attitude, internal and external pressure and consider future consequence positively effects the decision to adopt Green IT in organizations. This study also found that customer satisfaction, environment, and economic performance are significant factors in achieving sustainability. Thus, pro-environmental commitment and actions of the organizations drive green business activities. Through this research, the study recommends further investigation of the relationship among the motivation factors as well as its implications for organizations' performance towards sustainability.
How We Watch TV Tomorrow?
Authors: Zhong Bu , Yang Fan
Published: January 2019

Smart TV is so called largely due to its interactivity. Without the interactivity functions, smart TV can hardly provide new services beyond traditional TV. This research studies 283 viewers' perceptions toward four key interactivity functions of smart TV: the interaction between viewers and TV, between viewers and friends, between viewers and programming, and viewers' interaction with products. The findings show that the viewer's residence was a significant moderator in the preference for the interactivity functions. Viewers from developed regions liked the four functions better than those in underdeveloped regions. Social media habits and ICT power usage are positively associated with the preference, while need for cognition, age and gender had little effect. The findings can help understand the evolving viewing habits in the social media era, whose theoretical and practical implications should benefit TV makers and content producers to provide an interactive TV viewing experience.
Factors That Influence Perceptions and Purchasing of Organic Produce by South African Consumers
Authors: Fynn-Green Geraldene , Mason Roger B , Giampiccoli Andrea
Published: January 2019

This article provides insight into the literature on consumer perceptions towards organic fruit and vegetables, attempting to identify factors that influence purchasing practices. Several supermarkets and fresh food markets in South Africa are now selling organically produced food items and consequently provide consumers with an alternative to conventionally grown food. However, limited research has been conducted in South Africa regarding consumer awareness and knowledge pertaining to organic produce and how consumer perceptions affect their purchasing practices. This article therefore provides a background to the organic food market in South Africa. From available literature, the article then goes on to explain the consumer behavior related to purchasing organic food produce, specifically with regard to socio-economic demographics and factors influencing willingness to pay a premium for organic produce. The article culminates in suggestions for further research to improve knowledge and understanding of the organic produce consumer in South Africa.
HIV, Cytomegalovirus, and Malaria Infections during Pregnancy Lead to Inflammation and Shifts in Memory B Cell Subsets in Kenyan Neonates
Authors: Yeo Kee Thai , Embury Paula , Anderson Timothy , Mungai Peter , Malhotra Indu , King Christopher , Kazura James , Dent Arlene
Published: January 2019

Infections during pregnancy can expose the fetus to microbial Ags, leading to inflammation that affects B cell development. Prenatal fetal immune priming may have an important role in infant acquisition of pathogen-specific immunity. We examined plasma proinflammatory biomarkers, the proportions of various B cell subsets, and fetal priming to tetanus vaccination in cord blood from human United States and Kenyan neonates. United States neonates had no identified prenatal infectious exposures, whereas Kenyan neonates examined had congenital CMV or mothers with prenatal HIV or Plasmodium falciparum or no identified infectious exposures. Kenyan neonates had higher levels of IP-10, TNF-α, CRP, sCD14, and BAFF than United States neonates. Among the Kenyan groups, neonates with prenatal infections/infectious exposures had higher levels of cord blood IFN-γ, IL-7, sTNFR1, and sTNFR2 compared with neonates with no infectious exposures. Kenyan neonates had greater proportions of activated memory B cells (MBC) compared with United States neonates. Among the Kenyan groups, HIV-exposed neonates had greater proportions of atypical MBC compared with the other groups. Although HIV-exposed neonates had altered MBC subset distributions, detection of tetanus-specific MBC from cord blood, indicative of fetal priming with tetanus vaccine given to pregnant women, was comparable in HIV-exposed and non–HIV-exposed neonates. These results indicate that the presence of infections during pregnancy induces fetal immune activation with inflammation and increased activated MBC frequencies in neonates. The immunologic significance and long-term health consequences of these differences warrant further investigation.
MYMD-1, a Novel Immunometabolic Regulator, Ameliorates Autoimmune Thyroiditis via Suppression of Th1 Responses and TNF-α Release
Authors: Di Dalmazi Giulia , Chalan Paulina , Caturegli Patrizio
Published: January 2019

MYMD-1 is a synthetic derivative of tobacco alkaloids, compounds that possess immunoregulatory properties and have been linked to the epidemiological observation that smoking reduces the odds of developing thyroid Abs and hypothyroidism. To assess the effect and mechanism(s) of the action of MYMD-1, we chose the NOD.H-2h4 mouse model of spontaneous thyroiditis. We began in vitro using T cells isolated from NOD.H-2h4 spleens and found that MYMD-1 suppressed TNF-α production by CD4+ T cells in a dose-dependent manner. We then treated 58 NOD.H-2h4 mice for 12 wk with either unsupplemented water that contained (10 mice) or did not contain (16 mice) MYMD-1 (185 mg/l) or water supplemented with sodium iodide (500 mg/l) that contained (16 mice) or did not contain (16 mice) MYMD-1. Mice were bled at baseline and then every 2 wk until sacrifice. MYMD-1 decreased the incidence and severity (p < 0.001) of thyroiditis, as assessed by histopathology. Similarly, the number of CD3+ T cells and CD19+ B cells infiltrating the thyroid was dampened by MYMD-1, as assessed by flow cytometry. Interestingly, the subset of thyroidal CD3+CD4+Tbet+RORγT− effector Th1 cells and the systemic levels of TNF-α were decreased by MYMD-1. Serum thyroglobulin Abs decreased in the MYMD-1 group. Thyroid hormones did not differ among the four groups, whereas thyroid-stimulating hormone increased upon iodine supplementation but remained normal in MYMD-1–treated mice. Overall, the study suggests that MYMD-1 ameliorates thyroiditis acting on specific lymphoid subsets. Further studies, including other models of autoimmunity, will confirm the potential clinical use of MYMD-1 as a novel immunometabolic regulator.
Anticorps et protéines, leurs liaisons dans le sérum antirouget
Authors: Basset Jean
Published: January 2019

Partant d’un sérum, antimicrobien : sérum antirouget obtenu d’un Cheval en puissance d’hyperimmunité maximale, nous avons à nouveau recherché les liaisons qu’entretiennent, avec les anticorps spécifiques, les protéines sériques séparées par M. Piettre avec sa méthode à l’acétone aux basses températures. Les résultats confirment ceux que nous avons publiés ici-même en 1946 :

L'immunisine est liée aux deux principales protéines, mais dans des proportions très différentes. Par rapport au sérum entier, l’albumine supporte environ fio p. ioo du pouvoir préventif ; la globuline 10 ou 20 p. 100 tout au plus.

L’agglutinine est liée tout entière à l’albumine. Les globulines sont dépourvues de la qualité floculante.

Ce fait que, dans tel sérum antimicrobien comme dans les sérums anti toxiques, c’est une même protéine qui supporte la majeure partie de l’anticorps immunisant, vient appuyer l’opinion dès longtemps exprimée par l’auteur : «Chez les Bactéries des infections septicémiques, l’antigène immu- nigène s’apparente à la toxine dite soluble des Bactéries essentiellement toxinogènes». «Dans toutes les infections bactériennes, l’immunité acquise est de nature antitoxique.»

Nos résultats prouvent encore que l’on n’est point autorisé à localiser dans les globulines la majeure partie des anticorps circulants : dans notre sérum antirouget, les globulines ne possèdent aucun pouvoir agglutinant.

Ils prouvent enfin que les sérums thérapeutiques ne sauraient être titrés in vitro par l’agglutination.
New type of evidence for secondary ice formation at around −15 °C in mixed-phase clouds
Authors: Mignani Claudia , Creamean Jessie M. , Zimmermann Lukas , Alewell Christine , Conen Franz
Published: January 2019

Abstract. Ice crystal numbers can exceed the numbers of ice-nucleating
particles (INPs) observed in mixed-phase clouds (MPCs) by several orders of
magnitude, also at temperatures that are colder than −8 ∘C. This
disparity provides circumstantial evidence of secondary ice formation, also
other than via the Hallett–Mossop process. In a new approach, we made use of
the fact that planar, branched ice crystals (e.g. dendrites) grow within a
relatively narrow temperature range (i.e. −12 to −17 ∘C) and can
be analysed individually for INPs using a field-deployable drop-freezing
assay. The novelty of our approach lies in comparing the growth temperature
encoded in the habit of an individual crystal with the activation temperature
of the most efficient INP contained within the same crystal to tell whether
it may be the result of primary ice formation. In February and March 2018, we
analysed a total of 190 dendritic crystals (∼3 mm median size)
deposited within MPCs at the high-altitude research station Jungfraujoch
(3580 m a.s.l.). Overall, one in eight of the analysed crystals contained
an INP active at −17 ∘C or warmer, while the remaining seven most
likely resulted from secondary ice formation within the clouds. The ice
multiplication factor we observed was small (8), but relatively stable
throughout the course of documentation. These measurements show that
secondary ice can be observed at temperatures around −15 ∘C and
thus advance our understanding of the extent of secondary ice formation in
MPCs, even where the multiplication factor is smaller than 10.
Photochemical Production of Ozone and Emissions of NOx and CH4 in the San Joaquin Valley
Authors: Trousdell Justin F. , Caputi Dani , Smoot Jeanelle , Conley Stephen A. , Faloona Ian C.
Published: January 2019

Abstract. Midday summertime flight data collected in the atmospheric boundary layer (ABL) of California's San Joaquin Valley (SJV) are used to investigate the scalar budgets of NOx, O3, and CH4 in order to quantify the individual processes that control near surface concentrations yet are difficult to constrain from surface measurements alone: most importantly, horizontal advection and entrainment mixing from above. The setting is a large mountain-valley system with a small aspect ratio where topography and persistent temperature inversions impose strong restraints on ABL ventilation. In conjunction with the observed time rate of change this airborne budgeting technique enables us to deduce net photochemical ozone production rates and emission fluxes of NOx and CH4. Measured NOx emissions from our principal flight domain were 216 (±33) metric tons/day averaged over six flights in July and August, which is nearly double the California government's NOx inventory for the surrounding three county region. We consider several possibilities for this discrepancy including the influence of wildfires, the temporal bias of the airborne sampling, instrumental interferences, and the recent hypothesis presented by Almaraz et al. (2018) of localized high soil NO emissions from intensive agricultural application of nitrogen fertilizers in the region and find the latter to be the most likely explanation. The methane emission average was 438 Gigagrams/year (±143), which exceeds an emissions inventory for the region by almost a factor of two as well. Measured ABL ozone during the six afternoon flights averaged 74 ppb (𝜎 = 9.8 ppb). The average mid-afternoon ozone rise of 2.8 ppb/h was found to be comprised of −0.8 ppb/h due to horizontal advection of lower O3 levels upwind, −2.2 ppb/h from dry deposition loss, −0.5 ppb/h from dilution by entrainment mixing, and 6.7 ppb/h net in-situ photochemical production. The O3 production rates exhibited a dependence on NO2 concentrations (r2 = 0.35), and no discernible dependence on methane concentrations (r2 ~ 0.02) which are correlated with many of the dominant VOC's in the region, suggesting that the ozone chemistry was predominantly NOx-limited on these flight days. Additionally, in order to determine the heterogeneity of the different scalars autocorrelation lengths were calculated for potential temperature (18 km), water vapor (18 km), ozone (30 km), methane (27 km), and NOx (28 km). The spatially diffuse pattern of CH4 and NOx seem to imply a preponderance of broad areal sources rather than localized emissions from cities and/or highway traffic within the SJV.
Characterizations and source analysis of atmospheric inorganic ions
at a national background site in the northeastern Qinghai-Tibet
Plateau: insights into the influence of anthropogenic emissions on a
high-altitude area of China
Authors: Han Bin , Wang Jing , Zhao Xueyan , Yin Baohui , Wang Xinhua , Dou Xiaoyan , Yang Wen , Bai Zhipeng
Published: January 2019

Abstract. Atmospheric particulate matter (PM) imposes highly uncertain impacts on both radiative forcing and human health. While ambient PM has been comprehensively characterized in China’s megacities; its composition, source, and characteristics in the Qinghai-Tibet Plateau (QTP) are not yet fully understood. An autumn observational campaign was conducted during the 1st–15th October 2013 at a national background monitoring station (3295 m a.s.l.) in the QTP. Real time concentrations of inorganic water-soluble ions (WSIs) associated with PM2.5 were measured in addition to PM2.5 concentrations, gaseous pollutants, and meteorological parameters. SO42− was the most abundant WSI (10.00 ± 4.39 μg/m3) followed by NH4+ (2.02 ± 0.93 μg/m3), and NO3− (1.65 ± 0.71 μg/m3). Observed WSI concentrations were lower as compared to urban sites in eastern China; however, they were higher as compared to other QTP monitoring sites. High sulfate and nitrate oxidation ratios indicated strong secondary formation of both SO42− and NO3−. Both photochemical and heterogeneous reactions contributed to the formation of particulate SO42−, while the conversion of NO2 to NO3− only occurred via photochemical reactions in the presence of high O3 concentrations and strong sunlight. Correlation analysis between WSIs revealed that NH4NO3, (NH4)2SO4, Na2SO4, and K2SO4 were the major atmospheric aerosol components. To better understand the potential sources of WSIs in the QTP, a Positive Matrix Factorization receptor model was used. Results showed that salt lake emissions, mixed factor emissions (livestock feces emission, occasional biomass burning, and crustal material), traffic emissions, secondary inorganic aerosols, and residential burning were the major emission sources at the study site.
Converting Snow Depth to Snow Water Equivalent Using
Climatological Variables
Authors: Hill David F. , Burakowski Elizabeth A. , Crumley Ryan L. , Keon Julia , Hu J. Michelle , Arendt Anthony A. , Wikstrom Jones Katreen , Wolken Gabriel J.
Published: January 2019

Abstract. We present a simple method that allows snow depth measurements to be converted to snow water equivalent (SWE) estimates. These estimates are useful to individuals interested in water resources, ecological function, and avalanche forecasting. They can also be assimilated into models to help improve predictions of total water volumes over large regions. The conversion of depth to SWE is particularly valuable since snow depth measurements are far more numerous than costlier and more complex SWE measurements. Our model regresses SWE against snow depth and climatological (30-year normal) values for mean annual precipitation (MAP) and mean February temperature, producing a power-law relationship. Relying on climatological normals rather than weather data for a given year allows our model to be applied at measurement sites lacking a weather station. Separate equations are obtained for the accumulation and the ablation phases of the snowpack, which introduces day of water year (DOY) as an additional variable. The model is validated against a large database of snow pillow measurements and yields a bias in SWE of less than 0.5 mm and a root-mean-squared-error (RMSE) in SWE of approximately 65 mm. When the errors are investigated on a station-by-station basis, the average RMSE is about 5 % of the MAP at each station. The model is additionally validated against a completely independent set of data from the northeast United States. Finally, the results are compared with other models for bulk density that have varying degrees of complexity and that were built in multiple geographic regions. The results show that the model described in this paper has the best performance for the validation data set.
There is More to it Than Meets the Eye: An Intercultural Study of Religious Speech Acts between Jordanian and American Students
Authors: Almwajeh Motasim , Rababah Luqman
Published: January 2019

The purpose of this study is to investigate the use of religious utterances in everyday speech by Jordanian university students and those of U. S. university students. This study tries to compare and contrast the frequency of religious speech by Jordanian and American students in order to show cross-cultural similarities and variations, and to foreground connections among linguistic, cultural, and religious subtexts. The researchers contend that people, from various cultures paradigms, need to re-envision and reformulate their methods of interaction, both locally and globally. The study took place at IUP (Indiana University of Pennsylvania). Five Jordanian students and five American students are selected from various fields of study and specializations. They are mostly acquaintances who expressed their willingness to help with this study.  The researchers conducted ten personal interviews with all the participants, and each interview lasted about 30 minutes. The researchers chose to audio record the interviews because all the participants signed a consent form and thus gave us the permission to do so. All the participants are IUP students; most of them are undergraduate students, but three of them are doing graduate studies at Indiana University of Pennsylvania. Not only did the researchers hand each participant a copy of the questionnaire, but they also explained the questions to them and ascertained that they fully understood each question. The participants were presented with the same exact questions to see how they respond to these situations, and the researchers interpreted their responses and have come up with conclusions about the integration of religious language in the parameters of everyday speech used by U.S. and Jordanian students. Basically, the data collected delineates similarities and differences between respondents from both cultures and features intersections between religiously marked language and everyday speech.