bluuebunny/crossref_metadata_2025 huggingface dataset:
Molecular Signatures of the Insulin-Like Growth Factor 1-Mediated Epithelial-Mesenchymal Transition in Breast, Lung and Gastric Cancers
Authors: Cevenini Armando , Orrù Stefania , Mancini Annamaria , Alfieri Andreina , Buono Pasqualina , Imperlini Esther
Published: August 2018

The insulin-like growth factor (IGF) system, which is constituted by the IGF-1 and IGF-2 peptide hormones, their corresponding receptors and several IGF binding proteins, is involved in physiological and pathophysiological processes. The IGF system promotes cancer proliferation/survival and its signaling induces the epithelial-mesenchymal transition (EMT) phenotype, which contributes to the migration, invasiveness, and metastasis of epithelial tumors. These cancers share two major IGF-1R signaling transduction pathways, PI3K/AKT and RAS/MEK/ERK. However, as far as we could review at this time, each type of cancer cell undergoes EMT through tumor-specific routes. Here, we review the tumor-specific molecular signatures of IGF-1-mediated EMT in breast, lung, and gastric cancers.
Effect of Alloying Elements Gradient on Solid-State Diffusion Bonding between Aerospace Aluminum Alloys
Authors: Wu Fan , Zhou Wenlong , Han Yujie , Fu Xuesong , Xu Yanjin , Hou Hongliang
Published: August 2018

Three different bonding couples assembled by two commonly used aerospace aluminum alloys were bonded within the temperature range of 460–520 °C under 6 MPa for 60 min in vacuum atmosphere. The interface microstructure and alloying elements distribution of the bonded joints were determined by scanning electron microscope (SEM) and Energy Dispersive Spectroscope (EDS); the bond strength was evaluated by tensile-shear strength test. The results show the bond quality improved effectively as the bonding temperature increased. Compared with the 1420-1420 and 7B04-7B04 bonding couples, the 1420-7B04 couples obtained better interface integrity and higher bond strength, the highest shear strength for 1420-7B04 couple can be as high as 188 MPa when bonded at 520 °C. Special attention was focused on the 1420-7B04 couple, the diffusion coefficient of Mg at the original interface under different temperatures were investigated, the results show the diffusion coefficient increased obviously as the bonding temperature increased. A diffusion affected zone (DAZ) without continuous intermetallic phases formed due to the diffusion of alloying elements across the bonding interface. The combined action of temperature and alloying elements gradient resulted in the increase of alloying elements diffusion fluxes, which in turn promote the bonding quality through the accelerated shrinkage of interfacial voids.
A Dynamic Overview of Antimicrobial Peptides and Their Complexes
Authors: De Paula Viviane Silva , Valente Ana Paula
Published: August 2018

In this narrative review, we comprehensively review the available information about the recognition, structure, and dynamics of antimicrobial peptides (AMPs). Their complex behaviors occur across a wide range of time scales and have been challenging to portray. Recent advances in nuclear magnetic resonance and molecular dynamics simulations have revealed the importance of the molecular plasticity of AMPs and their abilities to recognize targets. We also highlight experimental data obtained using nuclear magnetic resonance methodologies, showing that conformational selection is a major mechanism of target interaction in AMP families.
Allylation of Orthoquinones Towards Annulated Polycyclic Aromatic Systems
Authors: Kędziorek Mariusz , Dobrzańska Liliana
Published: August 2018

Promising results of an efficient and convenient strategy for the annulation of polycyclic aromatic compounds (PACs), employing orthoquinones as starting material and comprising allylation, pinacol rearrangement, ring-closing metathesis (RCM), and one-pot reduction followed by Wagner-Meerwein rearrangement, are presented. The strategy involves introducing triallylborane prepared in situ in the allylation step. Moreover, a novel expedient method for the preparation of 9,10-diallylphenanthrene was introduced.
Intakes, Adequacy, and Biomarker Status of Iron, Folate, and Vitamin B12 in Māori and Non-Māori Octogenarians: Life and Living in Advanced Age: A Cohort Study in New Zealand (LiLACS NZ)
Authors: Pillay Danika , Wham Carol , Moyes Simon , Muru-Lanning Marama , Teh Ruth , Kerse Ngaire
Published: August 2018

Advanced-age adults may be at risk of iron, folate, and vitamin B12 deficiency due to low food intake and poor absorption. This study aimed to investigate the intake and adequacy of iron, folate, and vitamin B12 and their relationship with respective biomarker status. Face-to-face interviews with 216 Māori and 362 non-Māori included a detailed dietary assessment using 2 × 24-h multiple pass recalls. Serum ferritin, serum iron, total iron binding capacity, transferrin saturation, red blood cell folate, serum folate, serum vitamin B12 and hemoglobin were available at baseline. Regression techniques were used to estimate the association between dietary intake and biomarkers. The Estimated Average Requirement (EAR) was met by most participants (>88%) for dietary iron and vitamin B12 (>74%) but less than half (>42%) for folate. Increased dietary folate intake was associated with increased red blood cell (RBC) folate for Māori (p = 0.001), non-Māori (p = 0.014) and serum folate for Māori (p < 0.001). Folate intake >215 µg/day was associated with reduced risk of deficiency in RBC folate for Māori (p = 0.001). Strategies are needed to optimize the intake and bioavailability of foods rich in folate. There were no significant associations between dietary iron and vitamin B12 intake and their respective biomarkers, serum iron and serum vitamin B12.
Modelling Nutrients and Organics Removal by Biological Slow Filtration in Micro-Polluted Water Source Treatment
Authors: Zhang Chengjin , He Jian , Zheng Zheng
Published: August 2018

The biological slow filtration (BSF) system as a simple and efficient environmental technology has been widely applied in treatment of ‘micro-polluted’ water. At present, many related studies have focused on the removal efficiency of biological indicators (such as bacteria and viruses). However, there is less research on the removal performance of nutrients and organics in the BSF system. In this paper, we employed a lab-scale biological slow filter to study the removal efficiency and degradation mechanism of nutrients and organics. We proved through adsorption of filter layer at the early running stage and biodegradation at the later stage, the BSF system could achieve effective removal of NH3-N, TN, TP, CODMn and turbidity and the corresponding removal rates are 83.65%, 42.45%, 42.94%, 60.41% and 83.55%, respectively. Furthermore, we also explored the influence of four main factors (filtration rate, filter depth, hydraulic head and temperature) and their interactions on removal rates of nutrients and organics in the BSF system and obtained the optimal operating parameters as follows: filtration rate 0.1 m/h, filter depth 0.8 m, hydraulic head 0.64 m, temperature 26.06 °C. This study would provide a theoretical foundation for the actual application of biological slow filter in treatment of micro-polluted water in developing countries and offer an optimized basis for the design of operating conditions.
Building Detection from VHR Remote Sensing Imagery Based on the Morphological Building Index
Authors: You Yongfa , Wang Siyuan , Ma Yuanxu , Chen Guangsheng , Wang Bin , Shen Ming , Liu Weihua
Published: August 2018

Automatic detection of buildings from very high resolution (VHR) satellite images is a current research hotspot in remote sensing and computer vision. However, many irrelevant objects with similar spectral characteristics to buildings will cause a large amount of interference to the detection of buildings, thus making the accurate detection of buildings still a challenging task, especially for images captured in complex environments. Therefore, it is crucial to develop a method that can effectively eliminate these interferences and accurately detect buildings from complex image scenes. To this end, a new building detection method based on the morphological building index (MBI) is proposed in this study. First, the local feature points are detected from the VHR remote sensing imagery and they are optimized by the saliency index proposed in this study. Second, a voting matrix is calculated based on these optimized local feature points to extract built-up areas. Finally, buildings are detected from the extracted built-up areas using the MBI algorithm. Experiments confirm that our proposed method can effectively and accurately detect buildings in VHR remote sensing images captured in complex environments.
Multiscale and Multifeature Segmentation of High-Spatial Resolution Remote Sensing Images Using Superpixels with Mutual Optimal Strategy
Authors: Fu Zhongliang , Sun Yangjie , Fan Liang , Han Yutao
Published: August 2018

High spatial resolution (HSR) image segmentation is considered to be a major challenge for object-oriented remote sensing applications that have been extensively studied in the past. In this paper, we propose a fast and efficient framework for multiscale and multifeatured hierarchical image segmentation (MMHS). First, the HSR image pixels were clustered into a small number of superpixels using a simple linear iterative clustering algorithm (SLIC) on modern graphic processing units (GPUs), and then a region adjacency graph (RAG) and nearest neighbors graph (NNG) were constructed based on adjacent superpixels. At the same time, the RAG and NNG successfully integrated spectral information, texture information, and structural information from a small number of superpixels to enhance its expressiveness. Finally, a multiscale hierarchical grouping algorithm was implemented to merge these superpixels using local-mutual best region merging (LMM). We compared the experiments with three state-of-the-art segmentation algorithms, i.e., the watershed transform segmentation (WTS) method, the mean shift (MS) method, the multiresolution segmentation (MRS) method integrated in commercial software, eCognition9, on New York HSR image datasets, and the ISPRS Potsdam dataset. Computationally, our algorithm was dozens of times faster than the others, and it also had the best segmentation effect through visual assessment. The supervised and unsupervised evaluation results further proved the superiority of the MMHS algorithm.
Distributed Fiber Optic Sensors for the Monitoring of a Tunnel Crossing a Landslide
Authors: Minardo Aldo , Catalano Ester , Coscetta Agnese , Zeni Giovanni , Zhang Lei , Di Maio Caterina , Vassallo Roberto , Coviello Roberto , Macchia Giuseppe , Picarelli Luciano , Zeni Luigi
Published: August 2018

This work reports on the application of a distributed fiber-optic strain sensor for long-term monitoring of a railway tunnel affected by an active earthflow. The sensor has been applied to detect the strain distribution along an optical fiber attached along the two walls of the tunnel. The experimental results, relative to a two-year monitoring campaign, demonstrate that the sensor is able to detect localized strains, identify their location along the tunnel walls, and follow their temporal evolution.
Symmetric Double-Eye Structure in Hurricane Bertha (2008) Imaged by SAR
Authors: Zhang Guosheng , Perrie William
Published: August 2018

Internal dynamical processes play a critical role in hurricane intensity variability. However, our understanding of internal storm processes is less well established, partly because of fewer observations. In this study, we present an analysis of the hurricane double-eye structure imaged by the RADARSAT-2 cross-polarized synthetic aperture radar (SAR) over Hurricane Bertha (2008). SAR has the capability of hurricane monitoring because of the ocean surface roughness induced by surface wind stress. Recently, the C-band cross-polarized SAR measurements appear to be unsaturated for the high wind speeds, which makes SAR suitable for studies of the hurricane internal dynamic processes, including the double-eye structure. We retrieve the wind field of Hurricane Bertha (2008), and then extract the closest axisymmetric double-eye structure from the wind field using an idealized vortex model. Comparisons between the axisymmetric model extracted wind field and SAR observed winds demonstrate that the double-eye structure imaged by SAR is relatively axisymmetric. Associated with airborne measurements using a stepped-frequency microwave radiometer, we investigate the hurricane internal dynamic process related to the double-eye structure, which is known as the eyewall replacement cycle (ERC). The classic ERC theory was proposed by assuming an axisymmetric storm structure. The ERC internal dynamic process of Hurricane Bertha (2008) related to the symmetric double-eye structure here, which is consistent with the classic theory, is observed by SAR and aircraft.
Tourism’s Impacts on Rural Livelihood in the Sustainability of an Aging Community in Japan
Authors: Chen Bixia , Qiu Zhenmian , Usio Nisikawa , Nakamura Koji
Published: August 2018

Rural tourism, which is often interpreted as rural development initiatives, has been extensively studied in a Japanese context; however, this has been typically observed at a community level, and the host households were assumed as homogeneous. Therefore, this article explores rural tourism’s potential as a tool for territorial development in Japan, and augments established literature by studying how rural tourism contributes to sustainable livelihoods at the household level in an aging community and a developed economy. For this purpose, a qualitative study observed a farm inn group in the town of Noto, a Globally Important Agricultural Heritage System (GIAHS) site in Japan. Three hypotheses were tested: (1) rural tourism in a remote/isolated region has changed the host households’ livelihood assets; (2) the economic benefits from rural tourism are marginal to host households; and (3) the benefits other than income earnings exceed the economic benefits for aging communities. The residents’ quality of life has improved in this super-aging rural community, although the economic benefits are still marginal to most host households. Tourists have brought vitality to these remote villages, and a lack of young residents to inherit these farm inn businesses presents a bottleneck to the industry’s future development. Social capital should be strengthened by forming social networks with the local government and private sectors.
Nasal Planum Vasculopathy in a Scottish Terrier Dog Treated with Ciclosporin and Endonasal Stents
Authors: Sartori Roberta , Colombo Valeria , Colombo Silvia , Noli Chiara
Published: August 2018

A two-year-old, intact female Scottish Terrier presented with one-and-a-half-year history of erosive and ulcerative lesions affecting the nasal planum. Clinical appearance, history, histopathology, and response to therapy were suggestive of a rare vasculopathy of the nasal planum that has been previously described in Scottish Terrier dogs. In previously published reports, medical treatments of the disease had failed, leading to euthanasia of five dogs, while a short-term follow-up was available for one case that was controlled with prednisolone and ciclosporin. The dog reported herein was successfully treated with medical therapy consisting initially of a combination of ciclosporin and prednisolone and endonasal stents applied over the first six months. Stents were inserted in order to prevent abnormal scarring and nostril stenosis. More than one and a half years after diagnosis, the dog is still being administered ciclosporin once daily, breathes normally, and has an optimal quality of life.
Awareness-Based Recommendation by Passively Interactive Learning
Authors: Yamaguchi Tomohiro , Nishimura Takuma , Nagahama Shota , Takadama Keiki
Published: August 2018

In artificial intelligence and robotics, one of the important issues is to design human interface. There are two issues: One is the machine-centered interaction design. Another one is the human-centered interaction design. This research aims at the latter issue. This chapter presents the interactive learning system to assist positive change in the preference of a human toward the true preference. Then evaluation of the awareness effect is discussed. The system behaves passively to reflect the human intelligence by visualizing the traces of his/her behaviors. Experimental results showed that subjects are divided into two groups, heavy users and light users, and that there are different effects between them under the same visualizing condition. They also showed that the authors' system improves the efficiency for deciding the most preferred plan for both heavy users and light users. As future research directions, a probabilistic event and its basic recommendation way are discussed.
Fourth Industrial Revolution
Authors: Guerra Alicia Guerra , Sánchez de Gómez Lyda
Published: August 2018

We are at the beginning of the fourth industrial revolution. The authors understand that university education should embrace the keys to this scenario and do so immediately. Considering this fact, new university teaching should be supported by technological immersion, but also by a culture of proactivity and training in values. The third of these pillars achieves an unimaginable relevance in regards to this emerging industrial revolution, which aims to become the revolution of values. Within this context, the university must move into the practice of ethical values and offer training based on soft skills. Moreover, there is a path that links ethics with soft skills based on the synergy between the two. From this idea, the central objectives of this work are to propose a university model for educational innovation based on values that also includes the tools for its implementation. The chapter ends with a practical case for implementing the model at the fablab that the University of Extremadura has available for its students majoring in Information Technology Engineering.
From PWI to HBCU
Authors: Brown Karen H.
Published: August 2018

Using critical race theory and Freire's theoretical framework of oppression as a guide, this chapter discusses institutionalized oppression through the lens of the chapter's author. She provides a collection of lived experiences in the form of short narratives. These narratives begin with the author's experiences as a Black student at predominantly White institutions (PWIs). The author describes many firsts—the first time she was referred to by a White male classmate as a beneficiary of Affirmative Action as the reason for admission into college and not by her merit, experienced low expectations of her academic ability, was called the N-word, and her first encounter with racial profiling. She then details personal accounts of navigating academia as a Black female faculty member in predominantly White institutions (PWIs), Historically Black Colleges and Universities (HBCU), as well as other organizations. Freire's theoretical framework on oppression guides her reflection and discussion of these Black-on-Black encounters. She ends the chapter with a discussion of actions taken.
Analyzing University Exploitation of Diversity to Legitimize Hiring Discrimination
Authors: Hargrave Constance P.
Published: August 2018

This critical race counter-story chronicles a Black woman professor's candidacy for an associate dean position at a predominantly White institution. It is uncommon to hear the voices of those who have been marginalized and disenfranchised in the hiring process at a university. This counter-narrative disrupts the silencing of voices at the margin and challenges the master narrative of the university hiring process by giving voice to a Black woman professor's experience. Using covert racism, the researcher deconstructs the university's actions to operationalize a deficit narrative of her associate dean candidacy, while simultaneously espousing a commitment to diversity by increasing funding to an outreach program for students of color. The chapter concludes with a discussion of self-care. Black feminist thought provides the framework to understand how acts of self-care influenced the self-definition of the Black woman professor.
Distributed Parameter Systems Control and Its Applications to Financial Engineering
Authors: Rigatos Gerasimos G. , Siano Pierluigi
Published: August 2018

The chapter analyzes differential flatness theory for the control of single asset and multi-asset option price dynamics, described by PDE models. Through these control methods, stabilization of distributed parameter (PDE modelled) financial systems is achieved and convergence to specific financial performance indices are made possible. The main financial model used in the chapter is the Black-Scholes PDE. By applying semi-discretization and a finite differences scheme the single-asset (equivalently multi-asset) Black-Scholes PDE is transformed into a state-space model consisting of ordinary nonlinear differential equations. For this set of differential equations, it is shown that differential flatness properties hold. This enables one to solve the associated control problem and to stabilize the options' dynamics. By showing the feasibility of control of the single-asset (equivalently multi-asset) Black-Scholes PDE, it is proven that through selected purchases and sales during the trading procedure, the price of options can be made to converge and stabilize at specific reference values.
An Extension to the Delone and Mclean Information Systems Success Model and Validation in the Internet Banking Context
Authors: Jagannathan Veeraraghavan , Balasubramanian Senthilarasu , Natarajan Thamaraiselvan
Published: August 2018

The modern internet era opened a plethora of opportunities for doing business online. Internet banking (IB) is one such innovation that made great strides from its humble beginnings in the mid-1990s. It is important for bank practitioners to know the factors contributing to the success of new technology by customers to enable them to be better placed in the competitive segment. This study proposes an extension to the Delone and Mclean IS success model to evaluate information systems(IS) success in the context of internet banking, with security as a new dimension. Data was collected from 312 respondents. The results found that security is a key factor for IB success. Furthermore, the study found that the dimension system quality has not had any substantial effect on IB user satisfaction; however, security and information quality were found to influence user satisfaction. Based on the findings, some implications for research and practice were prescribed, in addition to directions for future researchers of IS success in the IB context.
Noise Trader
Authors: Cheng Po-Keng
Published: August 2018

This chapter briefly reviews the literature on the topics of noise traders in the financial market. The authors cover the no‐trade theorem under complete and competitive markets in the 1980s, the noise trader approach to finance in the 1990s, and recent studies from several approaches related to noise traders, such as heterogeneous agent models, investor sentiment, retail investors, experimental analysis, and extrapolation. Understanding and tackling the issues resulted from noise traders would be essential for us to realize how financial and economic markets work.
Safeguarding of ATM
Authors: Srinivasan Srividhya , Krishnamoorthy Priya , Koteeswaran Raghuraman
Published: August 2018

An automated teller machine (ATM) is a kiosk that is used widely for money transactions across the globe. Several banking sectors have showed interest in deploying ATMs. The cash dispenser system manages the transaction services with less manual effort. When it comes to deploying an ATM, two methods are practiced: onsite ATM and offsite ATM. Safeguarding cash kept inside the ATM is a challenge. Researchers suggested several built-in security measures to secure the money in ATMs. Nevertheless, burglars still loot the money. Some widely used looting methods include card skimming, cash trapping, and phishing. So, it is time to give intelligence to the ATM itself to react to the situation. Proposed is a system that implements the idea of making machines to identify the situation and perform actions accordingly. This mechanism is not only about giving intelligence to it, but also a cost-effective one.
Acceptance of E-Reverse Auction From the Buyer Perspective
Authors: Gumussoy Cigdem Altin , Gumussoy Bilal
Published: August 2018

E-reverse auction is an online, real-time dynamic auction between a buyer organization and a group of pre-qualified suppliers. There occurs a competitive environment, which can lead to great price reductions for the items auctioned. In addition, cycle-time savings for buyers and suppliers, growing markets, accessing to a larger pool of suppliers can be the other advantages. Using e-reverse auction also includes risks such as damaging supplier relationships and increasing the total cost of procurement. This leads to a resistance from internal users and suppliers in the use of e-reverse auction. In the chapter, a research model including risks and benefits of using e-reverse auction is proposed in order to understand the important factors in the decision to use e-reverse auction.
Benchmarking Performance Indicators of Indian Rail Freight by DEA Approach
Authors: Bhanot Neeraj , Singh Harwinder
Published: August 2018

The overall development of business operations logistics activities becomes more important for firms with the globalization of economy, and therefore performance measurement, being equally important. In order to break monopolistic control of Container Corporation of India (CONCOR), Indian Railways entered competition in the container segment in January 2006 through private-public participation for customer-centric competitiveness. The purpose of this chapter is to benchmark the performance indicators in CONCOR. A case study has been conducted employing super-efficiency models of data envelopment analysis (DEA) on secondary data of CONCOR container terminals from 1994-95 to 2015-16 for performance evaluation within CONCOR. The exercise identified efficiency trends fluctuating between 75.83% to 109.51% (CCR model) and 93.52% to 100% (BCC model) within CONCOR, owing to lack of operational planning and lack of efficient staff.
Digital Transformation Journeys in a Digitized Reality
Authors: Janssens Jurgen
Published: August 2018

Big data and digitization are among the most talked about concepts of the last years. Whereas big data has more concrete outcomes, digitization is still seen as far away future. Nowadays, however, the question is no longer how to prepare for the upcoming digitization. The question companies and organizations have to ask themselves is how to adapt to today's digitizing world. A correct translation of this strategy is equally important. It requires a dynamic silver lining, compatible with interactive work clusters and a hybrid organization. Typically, this results in a new way of working and an appropriate approach to power this way of working. The way of working needs to be adapted to the redefined borders between reactivity and proactivity, the need for real-time service, and the need for contextual adaptation. It needs to be designed for agility. To provide value, an organic compromise has to be found that answers the need for creative freedom and the need for a solid structure where guidance, management, and development of human capabilities is possible in a structured way.
How the Crowdsourcing Enhance the Co-Creation Into the Virtual Communities
Authors: Nedra Bahri Ammari
Published: August 2018

Co-creation is the process by which products, services, and experiences are jointly developed by companies, their partners, and the final consumer, leading to a new space where the value created would be shared. The aim of this chapter is to explain the contribution of crowdsourcing to facilitate co-creation in virtual communities and to demonstrate the consequences of this IT on the firm, namely the strength of the relationship, the productivity, the efficiency.
Comprehensible Explanation of Predictive Models
Authors: Robnik-Šikonja Marko
Published: August 2018

The most successful prediction models (e.g., SVM, neural networks, or boosting) unfortunately do not provide explanations of their predictions. In many important applications of machine learning, the comprehension of the decision process is of utmost importance and dominates the classification accuracy (e.g., in business and medicine). This chapter introduces general explanation methods that are independent of the prediction model and can be used with all classification models that output probabilities. It explains how the methods work and graphically explains models' decisions for new unlabeled cases. The approach is put in the context of applications from medicine, business, and macro-economy.
Decision Filed Theory
Authors: Shao Lan , Markkula Jouni
Published: August 2018

Human decision-making theories and formal models are increasingly used for developing advanced ICT-based intelligent systems and services. Decision filed theory (DFT) is one of the decision-making theories that has significant potential for practical applications in real-world decision-making situations. Successful empirical studied have shown that DFT theory is able to explain human decision-making behavior in real situations, and the model can be applied as a basis for ICT system and service design. In this chapter, the authors present the results of a systematic literature review conducted for analyzing and synthesizing the evidence of DFT development and its validated usage in different application areas. The results show that the interest in DFT and its applications has grown strongly during the last years. The basic model has been extended to cover more complex decision-making situations and its applications have been widening.
Profit Maximizing Network Modeling With Inventory and Capacity Considerations
Authors: Miller Tan , de Matta Renato
Published: August 2018

Developing integrated strategic, tactical, and operational manufacturing and distribution plans for the global supply chain of a large, international firm represents a formidable planning, as well as organizational undertaking. Moreover, to develop and execute plans that are not only integrated but which maximize profits on a global basis presents a challenge of far greater magnitude. The use of advanced optimization modeling-based analytics can generate keen insights for management decisions regarding sourcing, production, distribution, inventory, and demand management on supply chain networks. This includes scenario and contingency planning analyses of complex strategic trade-offs such as the optimal balance between inventory levels and reserve manufacturing capacity on a network. In this chapter, the authors illustrate how optimization models can support a firm's planning efforts for these and related supply chain business decisions.
Medical Diagnosis Based on Distance Measures Between Picture Fuzzy Sets
Authors: Dutta Palash
Published: August 2018

This article describes how most frequently uncertainty arises due to vagueness, imprecision, partial information, etc., are encountered in medical diagnosis. To deal with this type of uncertainty, initially fuzzy set theory (FST) was explored and accordingly, medical decision making became one of the most important and interesting areas of applications of FST. Interval valued fuzzy sets (IVFSs) and intuitionistic fuzzy sets (IFS's) were developed and successfully applied in different areas including medical diagnosis. Although, IFS forms a membership degree and a non-membership degree separately in such a way that sum of the two degrees must not exceed one, but one of the important and integral part i.e., degree of neutrality is not taken into consideration in IFS, which is generally occurred in medical diagnosis. In such circumstances, picture fuzzy set (PFS) can be considered as a strong mathematical tool, which adequate in situations when human opinions involved more answers of type: yes, abstain, no. For this purpose, this article, proposes some distance measures on PFS and studies some of its properties. Also, an attempt has been made to carry out medical diagnosis via the proposed distance measures on PFSs and exhibit the technique with a suitable case study. It is found that the distance measures make it possible to introduce weights of all symptoms and consequently patient can be diagnosed directly.
New FCM Segmentation Approach Based on Multi-Resolution Analysis
Authors: Benzian Yaghmorasan , Benamrane Nacéra
Published: August 2018

This article presents a modified Fuzzy C Means segmentation approach based on multi-resolution image analysis. Fuzzy C-Means standard methods are improved through fuzzy clustering at different image resolution levels by propagating fuzzy membership values pyramidally from a lower to a higher level. Processing at a lower resolution image level provides a rough pixel classification result, thus, a pixel is assigned to a cluster to which the majority of its neighborhood pixels belongs. The aim of fuzzy clustering with multi-resolution images is to avoid pixel misclassification according to the spatial cluster of the neighbourhood of each pixel in order to have more homogeneous regions and eliminate noisy regions present in the image. This method is tested particularly on samples and medical images with gaussian noise by varying multiresolution parameter values for better analysis. The results obtained after multi-resolution clustering are giving satisfactory results by comparing this approach with standard FCM and spatial FCM ones.
Novel Reliable Uncapacitated P-Hub Location Problems Under Uncertainty
Authors: Nematian Javad
Published: August 2018

Hubs are facilities to collect, arrange and distribute commodities in telecommunication networks, cargo delivery systems, etc. In this article, it will study two popular hub location problems (p-hub center and p-hub maximal covering problems) under uncertainty. First, novel reliable uncapacitated p-hub location problems are introduced based on considering the failure probability of hubs, in which the parameters are random fuzzy variables, but the decision variables are real variables. Then, the proposed hub location problems under uncertainty are solved by new methods using random fuzzy chance-constrained programming based on the idea of possibility theory. These methods can satisfy optimistic and pessimistic decision makers under uncertain framework. Finally, some benchmark problems are solved as numerical examples to clarify the described methods and show their efficiency.
Fujitsu HIKARI, a Healthcare Decision Support System based on Biomedical Knowledge
Authors: Villazon-Terrazas Boris , Garcia-Santa Nuria , San Miguel Beatriz , del Rey-Mejías Angel , Muria Juan Carlos , Seara Germán , Reneses Blanca , de la Torre Victor
Published: August 2018

Fujitsu HIKARI is an artificial intelligence solution to assist clinicians in medical decision making, developed in the context of a joint collaboration project between Fujitsu Laboratories of Europe and Hospital Clínico San Carlos. This decision support system leverages on data analytics combined with healthcare semantic information to provide health estimations for patients, improving care quality and personalized treatment. Fujitsu HIKARI stands on the shoulders of biomedical knowledge, which includes (i) theoretical knowledge extracted from scientific literature, domain expert knowledge, and health standards; and (ii) empirical knowledge extracted from real patient electronic health records. The theoretical knowledge combines a theoretical knowledge graph (TKG) and a biomedical document repository (BDR). The empirical knowledge is encoded in an empirical knowledge graph (EKG). One of the main functionalities of Fujitsu HIKARI is the patient mental health risks assessment, which is based on the exploitation of its underlying Biomedical Knowledge.
Low Temperature Electrical Transport Study on Polymer/Carbon-Fiber Composites: Analysis beyond Mott’s Transition
Authors: Yasin Shadi Shaikh
Published: August 2018

The low temperature DC electrical conductivity of laminated conductive polymer composites with different concentrations of carbon fibers as a filler has been investigated. The electrical behavior below 105 K for all concentrations could be explained in terms of 3D Mott’s model that is the hopping conductivity can be considered as the dominating charge transport mechanism. From this model, the hopping distance, the density of state at Fermi level, and the decay constant for this material were determined.
Bioactivity and Antibacterial Studies on Silver Nanoparticles Embedded Calcium Borosilicate Ceramics
Authors: Mariappan Chinnasamy Ramaraj , Kumar Alesh , Sarahan Baljeet
Published: August 2018

We report the structural, bioactivity and antibacterial effect of silver nanoparticle embedded calcium borosilicate ceramics obtained by a simple sol-gel route and post annealing approach. The structural properties were studied by means of powder X-ray diffraction (XRD), UV-visible, Fourier transform infrared (FTIR) and transmission electron microscopy (TEM). The glass-ceramic nature of the sample was confirmed by XRD and FTIR. TEM and UV spectrum reveal the Ag nanoparticle embedment on amorphous matrix. The hydroxyapatite layer formation is investigated by in-vitro approach using Dulbecco’s Modified Eagle’s Medium. The antibacterial effects were tested with different bacteria using an agar well diffusion method. Samples show good antibacterial effect without compromising the formation of hydroxyapatite.
Crystal Structure of the Labile Complex of IL-24 with the Extracellular Domains of IL-22R1 and IL-20R2
Authors: Lubkowski Jacek , Sonmez Cem , Smirnov Sergey V. , Anishkin Andriy , Kotenko Sergei V. , Wlodawer Alexander
Published: August 2018

Crystal structure of the ternary complex of human IL-24 with two receptors, IL-22R1 and IL-20R2, has been determined at 2.15 Å resolution. A crystallizable complex was created by a novel approach involving fusing the ligand with a flexible linker to the presumed low-affinity receptor, and coexpression of this construct in Drosophila S2 cells together with the presumed high-affinity receptor. This approach, which may be generally applicable to other multiprotein complexes with low-affinity components, was necessitated by the instability of IL-24 expressed by itself in either bacteria or insect cells. Although IL-24 expressed in Escherichia coli was unstable and precipitated almost immediately upon its refolding and purification, a small fraction of IL-24 remaining in the folded state was shown to be active in a cell-based assay. In the crystal structure presented here, we found that two cysteine residues in IL-24 do not form a predicted disulfide bond. Lack of structural restraint by disulfides, present in other related cytokines, is most likely reason for the low stability of IL-24. Although the contact area between IL-24 and IL-22R1 is larger than between the cytokine and IL-20R2, calculations show the latter interaction to be slightly more stable, suggesting that the shared receptor (IL-20R2) might be the higher-affinity receptor.
Sensitization in Aluminum Alloys: Effect on Acoustic Parameters
Authors: Chukwunonye C.U. , Jones Nicholas J. , Petculescu Gabriela
Published: August 2018

Velocity and attenuation of shear and longitudinal sound waves were measured as a function of sensitization level in AA5083-H116 and AA5456-H116 aluminum alloys using two different techniques: resonant ultrasound spectroscopy (RUS) and pulse echo (PE). The frequency range for RUS was 0.3 MHz to 1 MHz. For PE, longitudinal 3.5 MHz and shear 1 MHz transducers were used. Sensitization was artificially induced in the laboratory by isothermally heating specimens at temperatures of 120°C, 175°C, 185°C, and 240°C for fixed periods of time (12 h to 96 h, the longer times for the lower temperatures). Measurements were repeated after each heating sequence. The overall changes are reported as percent difference between the as received and the fully sensitized states. The quantity that was found to be most sensitive to the degree of sensitization in this study is the attenuation coefficient of longitudinal waves, αL. The measured change in αL exceeds 20%, with error bars within 1% to 4%. Despite the magnitude of the error bars, the αL vs. degree-of-sensitization curve is clear and smooth. The shear wave velocity changed by 1.2% to 1.5%, with error bars within 0.01% to 0.1%. The larger change was observed for the AA5456 alloy, which contains more Mg. The longitudinal wave velocity was found to change by 0.5% for the 5456 alloy, with error bars within 0.004% to 0.02%. The attenuation coefficient for shear waves was not measured. This study identifies multiple ultrasonic parameters that can be combined into a new, on-site, nondestructive tool for quantitatively monitoring the sensitization level in Mg-rich aluminum alloys, with possible extensions to other materials.
Characterization of aerosol composition, aerosol acidity, and organic acid partitioning at an agriculturally intensive rural southeastern US site
Authors: Nah Theodora , Guo Hongyu , Sullivan Amy P. , Chen Yunle , Tanner David J. , Nenes Athanasios , Russell Armistead , Ng Nga Lee , Huey L. Gregory , Weber Rodney J.
Published: August 2018

Abstract. The implementation of stringent emission regulations has resulted in the
decline of anthropogenic pollutants including sulfur dioxide (SO2),
nitrogen oxides (NOx), and carbon monoxide (CO). In contrast, ammonia
(NH3) emissions are largely unregulated, with emissions projected to
increase in the future. We present real-time aerosol and gas measurements
from a field study conducted in an agriculturally intensive region in the
southeastern US during the fall of 2016 to investigate how NH3 affects
particle acidity and secondary organic aerosol (SOA) formation via the
gas–particle partitioning of semi-volatile organic acids. Particle water and
pH were determined using the ISORROPIA II thermodynamic model and validated
by comparing predicted inorganic HNO3-NO3- and
NH3-NH4+ gas–particle partitioning ratios with measured values.
Our results showed that despite the high NH3 concentrations (average 8.1±5.2 ppb), PM1 was highly acidic with pH values ranging from 0.9
to 3.8, and an average pH of 2.2±0.6. PM1 pH varied by
approximately 1.4 units diurnally. Formic and acetic acids were the most
abundant gas-phase organic acids, and oxalate was the most abundant
particle-phase water-soluble organic acid anion. Measured particle-phase
water-soluble organic acids were on average 6 % of the total
non-refractory PM1 organic aerosol mass. The measured molar fraction of
oxalic acid in the particle phase (i.e., particle-phase oxalic acid molar
concentration divided by the total oxalic acid molar concentration) ranged
between 47 % and 90 % for a PM1 pH of 1.2 to 3.4. The measured oxalic acid
gas–particle partitioning ratios were in good agreement with their
corresponding thermodynamic predictions, calculated based on oxalic acid's
physicochemical properties, ambient temperature, particle water, and pH. In
contrast, gas–particle partitioning ratios of formic and acetic acids were not well
predicted for reasons currently unknown. For this study, higher NH3
concentrations relative to what has been measured in the region in previous
studies had minor effects on PM1 organic acids and their influence on
the overall organic aerosol and PM1 mass concentrations.
Nepal Ambient Monitoring and Source Testing Experiment (NAMaSTE): Emissions
of particulate matter and sulfur dioxide from vehicles and brick kilns and their
impacts on air quality in the Kathmandu Valley, Nepal
Authors: Zhong Min , Saikawa Eri , Avramov Alexander , Chen Chen , Sun Boya , Ye Wenlu , Keene William C. , Yokelson Robert J. , Jayarathne Thilina , Stone Elizabeth A. , Rupakheti Maheswar , Panday Arnico K.
Published: August 2018

Abstract. Air pollution is one of the most pressing environmental issues in the Kathmandu Valley, where the capital city of Nepal is located. We estimated emissions from two of the major source types in the valley (vehicles and brick kilns) and analyzed the corresponding impacts on regional air quality. First, we estimated the on-road vehicle emissions in the valley using the International Vehicle Emission (IVE) model with local emission factors and the latest available data for vehicle registration. We also identified the locations of the brick kilns in the Kathmandu Valley and developed an emissions inventory for these kilns using emission factors measured during the Nepal Ambient Monitoring and Source Testing Experiment (NAMaSTE) field campaign in April 2015. Our results indicate that the commonly-used global emissions inventory, the Hemispheric Transport of Air Pollution (HTAP_v2.2), underestimates particulate matter emissions from vehicles in the Kathmandu Valley by a factor greater than 100. In addition, brick kilns account for nearly 70 % of total sulfur dioxide (SO2) emissions from all sectors considered in HTAP_v2.2. Next, we simulated air quality using the Weather Research and Forecasting model coupled with Chemistry (WRF-Chem) for April 2015 based on three different emission scenarios: HTAP only, HTAP with updated vehicle emissions, and HTAP with both updated vehicle and brick kilns emissions. Comparisons between simulated results and observations indicate that the model underestimates observed surface elemental carbon (EC) and SO2 concentrations under all emissions scenarios. However, our updated estimates of vehicle emissions significantly reduced model bias for EC, while updated emissions from brick kilns improved model performance in simulating SO2. These results highlight the importance of improving local emissions estimates for air quality modeling. We further find that model overestimation of surface wind leads to underestimated air pollutant concentrations in the Kathmandu Valley. Future work should focus on improving local emissions estimates for other major and underrepresented sources (e.g., crop residue burning and garbage burning) with a high spatial resolution, as well as the model's boundary-layer representation, to capture strong spatial gradients of air pollutant concentrations.
Mineralogy and mixing state of North African mineral dust by on-line single-particle mass spectrometry
Authors: Marsden Nicholas A. , Ullrich Romy , Möhler Ottmar , Eriksen Hammer Stine , Kandler Konrad , Cui Zhiqiang , Williams Paul I. , Flynn Michael J. , Liu Dantong , Allan James D. , Coe Hugh
Published: August 2018

Abstract. The mineralogy and mixing state of dust particles originating from the African continent influences climate and marine ecosystems in the North Atlantic due to its effect on radiation, cloud properties and biogeochemical cycling. Single-particle mineralogy and mixing state is particularly important in many processes but is difficult to predict because of large temporal and spatial variability and the lack of in-situ measurements of dust properties during emission, transport and deposition. This lack of measurements is in part due to the remoteness of potential source areas (PSA) and transport pathways, but also because of the lack of an efficient method to report the mineralogy and mixing state of single particles with a time resolution comparable to atmospheric processes. In this work, the mineralogy and mixing state of the fine fraction (