bluuebunny/crossref_metadata_2025 huggingface dataset:
Surface Science and Some of the Surface Analytical Techniques
Authors: Acharya Ananta Raj
Published: February 2018

Not available.Key words: Surface scienceThe Himalayan Physics  Vol.1, No.1, May, 2010 Page:54-57 Uploaded Date: 28 July, 2011
Quantum Optics: An Introduction
Authors: Lamsal Min Raj
Published: February 2018

Not available.Key words: Quantum OpticsThe Himalayan PhysicsVol.1, No.1, May, 2010 Page: 69-72 Uploaded Date: 28 July, 2011
History and Facts about Black Holes
Authors: Khatiwoda Devandra
Published: February 2018

Not available.Key words: Black holesThe Himalayan PhysicsVol.1, No.1, May, 2010 Page: 90-92 Uploaded Date: 28 July, 2011
Need of Quantum Mechanics
Authors: Tiwari Bishow Raj
Published: February 2018

Not available.Key words: MechanicsThe Himalayan PhysicsVol.1, No.1, May, 2010Page: 106-107Uploaded Date: 29 July, 2011
Electromagnetic Mass and Violation of Newton's Law
Authors: Acharya Shreeram
Published: February 2018

Not available.Key words: Newton's LawThe Himalayan Physics Vol.1, No.1, May, 2010 Page: 97-98 Uploaded Date: 28 July, 2011
Splenic Volume: Correlation between Ultrasonogram and Standard CT Measurements
Authors: Paul Fonindra Nath , Taher Md. Abu , Jahan Mahood -uz- , Roy Shyamal Kumar , Sarkar Snigdha , Sultana Sohely
Published: February 2018

Evaluation of splenic enlargement is important in the diagnosis and management of various diseases including liver disease, lymphoma and other primary or metastatic neoplasm. This cross sectional study was conducted in the department of radiology and imaging in Bangladesh Institute of Research and Rehabilitation in Diabetes, Endocrine and Metabolic Disorders (BIRDEM) from July 2007 to June 2009. The main objective of the study was to find out a more accurate sonographic measurement of splenic volume that well correlate with gold standard computed tomography (CT) volume. A total of 228 subjects were included in the study. All the subjects underwent ultrasound and CT examinations for measurement of splenic volume. The mean splenic volume measured by AVL (average length) was 182.62±80.28 cm3 (mean±SD) with range of 45.61-590.93 cm3 and by CT scan was 190.18±77.77 cm3 (mean±SD) with range of 46.52-565.81cm3. Most of the subjects 138(60.5%) had splenic volume 101-200 cm3. Splenic volume was evaluate by CT findings of 228 cases and expressed in cm3. Sonographic splenic volumes were calculated by using the prolate Ellipsoid method AVL (average length) and also expressed in cm3.The mean difference of splenic volume evaluated by CT and sonography was 7.43±5.39 cm3 with standard deviation of 5.39 cm3 measured from average length (AVL). The mean difference of splenic volume evaluated by two modalities measured by average length was statistically significant (pp<0.001).
Phosphorus Transport in Arabidopsis and Wheat: Emerging Strategies to Improve P Pool in Seeds
Authors: Kisko Mushtak , Shukla Vishnu , Kaur Mandeep , Bouain Nadia , Chaiwong Nanthana , Lacombe Benoit , Pandey Ajay , Rouached Hatem
Published: February 2018

Phosphorus (P) is an essential macronutrient for plants to complete their life cycle. P taken up from the soil by the roots is transported to the rest of the plant and ultimately stored in seeds. This stored P is used during germination to sustain the nutritional demands of the growing seedling in the absence of a developed root system. Nevertheless, P deficiency, an increasing global issue, greatly decreases the vigour of afflicted seeds. To combat P deficiency, current crop production methods rely on heavy P fertilizer application, an unsustainable practice in light of a speculated decrease in worldwide P stocks. Therefore, the overall goal in optimizing P usage for agricultural purposes is both to decrease our dependency on P fertilizers and enhance the P-use efficiency in plants. Achieving this goal requires a robust understanding of how plants regulate inorganic phosphate (Pi) transport, during vegetative growth as well as the reproductive stages of development. In this short review, we present the current knowledge on Pi transport in the model plant Arabidopsis thaliana and apply the information towards the economically important cereal crop wheat. We highlight the importance of developing our knowledge on the regulation of these plants’ P transport systems and P accumulation in seeds due to its involvement in maintaining their vigour and nutritional quality. We additionally discuss further discoveries in the subjects this review discusses substantiate this importance in their practical applications for practical food security and geopolitical applications.
Inkjet-Printed and Paper-Based Electrochemical Sensors
Authors: Tortorich Ryan , Shamkhalichenar Hamed , Choi Jin-Woo
Published: February 2018

It is becoming increasingly more important to provide a low-cost point-of-care diagnostic device with the ability to detect and monitor various biological and chemical compounds. Traditional laboratories can be time-consuming and very costly. Through the combination of well-established materials and fabrication methods, it is possible to produce devices that meet the needs of many patients, healthcare and medical professionals, and environmental specialists. Existing research has demonstrated that inkjet-printed and paper-based electrochemical sensors are suitable for this application due to advantages provided by the carefully selected materials and fabrication method. Inkjet printing provides a low cost fabrication method with incredible control over the material deposition process, while paper-based substrates enable pump-free microfluidic devices due to their natural wicking ability. Furthermore, electrochemical sensing is incredibly selective and provides accurate and repeatable quantitative results without expensive measurement equipment. By merging each of these favorable techniques and materials and continuing to innovate, the production of low-cost point-of-care sensors is certainly within reach.
Modular Continuum Manipulator: Analysis and Characterization of Its Basic Module
Authors: Mishra Anand Kumar , Mondini Alessio , Del Dottore Emanuela , Sadeghi Ali , Tramacere Francesca , Mazzolai Barbara
Published: February 2018

We present the basic module of a modular continuum arm (soft compliant manipulator for broad applications (SIMBA)). SIMBA is a robotic arm with a hybrid structure, namely a combination of rigid and soft components, which makes the arm highly versatile, dexterous, and robust. These key features are due to the design of its basic module, which is characterized by a three-dimensional workspace with a constant radius around its rotation axis, large and highly repeatable bending, complete rotation, and passive stiffness. We present an extensive analysis and characterization of the basic module of the SIMBA arm in terms of design, fabrication, kinematic model, stiffness, and bending behavior. All the theoretical models presented were validated with empirical results. Our findings show a positional typical error of less than ≈6% in module diameter (highly repeatable) with a passive stiffness of 0.8 N/mm (≈1 kg load). Our aim is to demonstrate that this kind of robotic element can be exploited as an elementary module of a more complex structure, which can be used in any application requiring high directional stiffness but without the need for an active stiffness mechanism, as is the case in daily activities (e.g., door opening, water pouring, obstacle avoidance, and manipulation tasks).
Catalytic Fast Pyrolysis of Kraft Lignin over Hierarchical HZSM-5 and Hβ Zeolites
Authors: Bi Yadong , Lei Xiaojuan , Xu Guihua , Chen Hui , Hu Jianli
Published: February 2018

The hierarchical HZSM-5 and Hβ zeolites were prepared by alkaline post-treatment methods adopting Na2CO3, TMAOH/NaOH mixture, and NaOH as desilication sources, respectively. More mesopores are produced over two kinds of zeolites, while the micropores portion is well preserved. The mesopores formed in hierarchical Hβ zeolites were directly related to the basicity of the alkaline solution, indicating that Hβ zeolite is more sensitive to the alkaline post-treatment. The hierarchical HZSM-5 and Hβ zeolites are more active than the parent one for catalytic fast pyrolysis (CFP) of Kraft lignin. Hierarchical zeolites retained the function of acid catalysis, while additionally creating larger mesopores to ensure the entry of bulkier reactant molecules. The increase of the condensable volatiles yield can be attributed to the improvement of the mass transfer performance, which correlates well with the change of mesoporous surface area. In particular, the condensable volatiles yield for the optimized hierarchical Hβ reached approximately two times that of the parent Hβ zeolites. In contrast to the parent HZSM-5, the optimized hierarchical HZSM-5 zeolite significantly reduced the selectivity of oxygenates from 27.2% to 3.3%.
A Power System Network Splitting Strategy Based on Contingency Analysis
Authors: Saharuddin Nur , Zainal Abidin Izham , Mokhlis Hazlie , Abdullah Abdul , Naidu Kanendra
Published: February 2018

This paper proposes a network splitting strategy following critical line outages based on N-1 contingency analysis. Network splitting is the best option for certain critical outages when the tendency of severe cascading failures is very high. Network splitting is executed by splitting the power system network into feasible set of islands. Thus, it is essential to identify the optimal splitting solution (in terms of minimal power flow disruption) that satisfies certain constraints. This paper determines the optimal splitting solution for each of the critical line outage using discrete evolutionary programming (DEP) optimization technique assisted by heuristic initialization approach. Heuristic initialization provides the best initial cutsets which will guide the optimization technique to find the optimal splitting solution. Generation–load balance and transmission line overloading analysis are carried out in each island to ensure the steady state stability is achieved. Load shedding scheme is initiated if the power balance criterion is violated in any island to sustain the generation–load balance. The proposed technique is validated on the IEEE 118 bus system. Results show that the proposed approach produces an optimal splitting solution with lower power flow disruption during network splitting execution.
Unitary Issues in Some Higher Derivative Field Theories
Authors: Asorey Manuel , Rachwal Leslaw , Shapiro Ilya
Published: February 2018

We analyze the unitarity properties of higher derivative quantum field theories which are free of ghosts and ultraviolet singularities. We point out that in spite of the absence of ghosts most of these theories are not unitary. This result confirms the difficulties of finding a consistent quantum field theory of quantum gravity.
Genome Size Diversity and Its Impact on the Evolution of Land Plants
Authors: Pellicer Jaume , Hidalgo Oriane , Dodsworth Steven , Leitch Ilia
Published: February 2018

Genome size is a biodiversity trait that shows staggering diversity across eukaryotes, varying over 64,000-fold. Of all major taxonomic groups, land plants stand out due to their staggering genome size diversity, ranging ca. 2400-fold. As our understanding of the implications and significance of this remarkable genome size diversity in land plants grows, it is becoming increasingly evident that this trait plays not only an important role in shaping the evolution of plant genomes, but also in influencing plant community assemblages at the ecosystem level. Recent advances and improvements in novel sequencing technologies, as well as analytical tools, make it possible to gain critical insights into the genomic and epigenetic mechanisms underpinning genome size changes. In this review we provide an overview of our current understanding of genome size diversity across the different land plant groups, its implications on the biology of the genome and what future directions need to be addressed to fill key knowledge gaps.
PClass: Protein Quaternary Structure Classification by Using Bootstrapping Strategy as Model Selection
Authors: Huang Chi-Chou , Chang Chi-Chang , Chen Chi-Wei , Ho Shao-yu , Chang Hsung-Pin , Chu Yen-Wei
Published: February 2018

Protein quaternary structure complex is also known as a multimer, which plays an important role in a cell. The dimer structure of transcription factors is involved in gene regulation, but the trimer structure of virus-infection-associated glycoproteins is related to the human immunodeficiency virus. The classification of the protein quaternary structure complex for the post-genome era of proteomics research will be of great help. Classification systems among protein quaternary structures have not been widely developed. Therefore, we designed the architecture of a two-layer machine learning technique in this study, and developed the classification system PClass. The protein quaternary structure of the complex is divided into five categories, namely, monomer, dimer, trimer, tetramer, and other subunit classes. In the framework of the bootstrap method with a support vector machine, we propose a new model selection method. Each type of complex is classified based on sequences, entropy, and accessible surface area, thereby generating a plurality of feature modules. Subsequently, the optimal model of effectiveness is selected as each kind of complex feature module. In this stage, the optimal performance can reach as high as 70% of Matthews correlation coefficient (MCC). The second layer of construction combines the first-layer module to integrate mechanisms and the use of six machine learning methods to improve the prediction performance. This system can be improved over 10% in MCC. Finally, we analyzed the performance of our classification system using transcription factors in dimer structure and virus-infection-associated glycoprotein in trimer structure. PClass is available via a web interface at http://predictor.nchu.edu.tw/PClass/.
Drugs and Mental Health Problems among the Roma: Protective Factors Promoted by the Iglesia Evangélica Filadelfia
Authors: López Jelen , García Ramón , Martí Teresa
Published: February 2018

Background: High incidences of drug consumption and mental health problems are found among the Roma population in Spain, a reality that remains understudied. Past studies have indicated the positive role played by the Iglesia Evangélica Filadelfia (IEF) in promoting rehabilitation and prevention of these practices. Objective: In this article, authors analyze in which ways the IEF favors processes of drug rehabilitation and mental health recovery as well as the prevention of these problems among its Roma members. Methods: A communicative qualitative approach was developed. It was communicative because new knowledge was created by dialogically contrasting the existing state of the art with study participants. It was qualitative because everyday life stories were collected, gathering the experiences, perceptions and interpretations of Roma people who are actively involved in three different IEF churches based in Barcelona. Results: This article identifies these protective factors: anti-drug discourse, a supportive environment, new social relations, role model status, the promotion of interactions, the revaluation of oneself, spiritual activities and the improvement of the feeling of belonging and the creation of meaning. Conclusion: The present research contributes new evidence to the current understanding of the role played by the IEF in improving Roma health status and how the identified protective factors can contribute to rehabilitation and recovery from such problems in other contexts.
Mental Health Interventions for Parent Carers of Children with Autistic Spectrum Disorder: Practice Guidelines from a Critical Interpretive Synthesis (CIS) Systematic Review
Authors: Catalano Denise , Holloway Linda , Mpofu Elias
Published: February 2018

Parent carers of children with Autism Spectrum Disorder (ASD) often report increased levels of stress, depression, and anxiety. Unmet parent carer mental health needs pose a significant risk to the psychological, physical, and social well-being of the parents of the child affected by ASD and jeopardize the adaptive functioning of the family as well as the potential of the child affected by ASD. This systematic review identifies key qualities of interventions supporting the mental health of parent carers and proposes practitioner-parent carer support guidelines. A search of four databases (Medline, PubMed, PsycINFO, and Social Science Data) was conducted to identify studies that met the following criteria: (1) an intervention was delivered to parent carers of a child with ASD under the age of 18 years; (2) the research design allowed for a comparison on outcomes across groups; and (3) outcome measures of the parent carers’ mental health were used. A total of 23 studies met the inclusion criteria. A critical interpretive synthesis approach was used to produce an integrated conceptualization of the evidence. Findings suggest practitioner guidelines to support the mental health and wellbeing of parent carers should include addressing the parent’s self-perspective taking and skill for real time problem-solving.
Alteration of Epigenetic Regulation by Long Noncoding RNAs in Cancer
Authors: Morlando Mariangela , Fatica Alessandro
Published: February 2018

Long noncoding RNAs (lncRNAs) are important regulators of the epigenetic status of the human genome. Besides their participation to normal physiology, lncRNA expression and function have been already associated to many diseases, including cancer. By interacting with epigenetic regulators and by controlling chromatin topology, their misregulation may result in an aberrant regulation of gene expression that may contribute to tumorigenesis. Here, we review the functional role and mechanisms of action of lncRNAs implicated in the aberrant epigenetic regulation that has characterized cancer development and progression.
Conformational Dynamics and Stability of U-Shaped and S-Shaped Amyloid β Assemblies
Authors: Grasso Gianvito , Rebella Martina , Muscat Stefano , Morbiducci Umberto , Tuszynski Jack , Danani Andrea , Deriu Marco
Published: February 2018

Alzheimer’s disease is the most fatal neurodegenerative disorder characterized by the aggregation and deposition of Amyloid β (Aβ) oligomers in the brain of patients. Two principal variants of Aβ exist in humans: Aβ1–40 and Aβ1–42. The former is the most abundant in the plaques, while the latter is the most toxic species and forms fibrils more rapidly. Interestingly, fibrils of Aβ1–40 peptides can only assume U-shaped conformations while Aβ1–42 can also arrange as S-shaped three-stranded chains, as recently discovered. As alterations in protein conformational arrangement correlate with cell toxicity and speed of disease progression, it is important to characterize, at molecular level, the conformational dynamics of amyloid fibrils. In this work, Replica Exchange Molecular Dynamics simulations were carried out to compare the conformational dynamics of U-shaped and S-shaped Aβ17–42 small fibrils. Our computational results provide support for the stability of the recently proposed S-shaped model due to the maximized interactions involving the C-terminal residues. On the other hand, the U-shaped motif is characterized by significant distortions resulting in a more disordered assembly. Outcomes of our work suggest that the molecular architecture of the protein aggregates might play a pivotal role in formation and conformational stability of the resulting fibrils.
Protease-Activated Receptor 4 (PAR4): A Promising Target for Antiplatelet Therapy
Authors: Rwibasira Rudinga Gamariel , Khan Ghulam , Kong Yi
Published: February 2018

Cardiovascular diseases (CVDs) are currently among the leading causes of death worldwide. Platelet aggregation is a key cellular component of arterial thrombi and major cause of CVDs. Protease-activated receptors (PARs), including PAR1, PAR2, PAR3 and PAR4, fall within a subfamily of seven-transmembrane G-protein-coupled receptors (GPCR). Human platelets express PAR1 and PAR4, which contribute to the signaling transduction processes. In association with CVDs, PAR4 not only contributes to platelet activation but also is a modulator of cellular responses that serve as hallmarks of inflammation. Although several antiplatelet drugs are available on the market, they have many side effects that limit their use. Emerging evidence shows that PAR4 targeting is a safer strategy for preventing thrombosis and consequently may improve the overall cardiac safety profile. Our present review summarizes the PAR4 structural characteristics, activation mechanism, role in the pathophysiology of diseases and understanding the association of PAR4 targeting for improved cardiac protection. Conclusively, this review highlights the importance of PAR4 antagonists and its potential utility in different CVDs.
Bioactive Films Containing Alginate-Pectin Composite Microbeads with Lactococcus lactis subsp. lactis: Physicochemical Characterization and Antilisterial Activity
Authors: Bekhit Mariam , Arab-Tehrany Elmira , Kahn Cyril , Cleymand Franck , Fleutot Solenne , Desobry Stephane , Sánchez-González Laura
Published: February 2018

Novel bioactive films were developed from the incorporation of Lactococcus lactis into polysaccharide films. Two different biopolymers were tested: cellulose derivative (hydroxylpropylmethylcellulose (HPMC)) and corn starch. Lactic acid bacteria (LAB) free or previously encapsulated in alginate-pectin composite hydrogel microbeads were added directly to the film forming solution and films were obtained by casting. In order to study the impact of the incorporation of the protective culture into the biopolymer matrix, the water vapour permeability, oxygen permeability, optical and mechanical properties of the dry films were evaluated. Furthermore, the antimicrobial effect of bioactive films against Listeria monocytogenes was studied in synthetic medium. Results showed that the addition of LAB or alginate-pectin microbeads modified slightly films optical properties. In comparison with HPMC films, starch matrix proves to be more sensitive to the addition of bacterial cells or beads. Indeed, mechanical resistance of corn starch films was lower but barrier properties were improved, certainly related to the possible establishment of interactions between alginate-pectin beads and starch. HPMC and starch films containing encapsulated bioactive culture showed a complete inhibition of listerial growth during the first five days of storage at 5 °C and a reduction of 5 logs after 12 days.
Cytokeratin-8 in Anaplastic Thyroid Carcinoma: More Than a Simple Structural Cytoskeletal Protein
Authors: Guo Dehuang , Xu Qinqin , Pabla Sarabjot , Koomen John , Biddinger Paul , Sharma Ashok , Pabla Simarjot , Pacholczyk Rafal , Chang Chien-Chung , Friedrich Kevin , Mohammed Kamran , Smallridge Robert , Copland John , She Jin-Xiong , Weinberger Paul
Published: February 2018

Anaplastic thyroid carcinoma (ATC) is almost universally fatal. Elevated keratin-8 (KRT8) protein expression is an established diagnostic cancer biomarker in several epithelial cancers (but not ATC). Several keratins, including KRT8, have been suggested to have a role in cell biology beyond that of structural cytoskeletal proteins. Here, we provide evidence that KRT8 plays a direct role in the growth of ATCs. Genomic and transcriptomic analysis of >5000 patients demonstrates that KRT8 mutation and copy number amplification are frequently evident in epithelial-derived cancers. Carcinomas arising from diverse tissues exhibit KRT8 mRNA and protein overexpression when compared to normal tissue levels. Similarly, in a panel of patient-derived ATC cell lines and patient tumors, KRT8 expression shows a similar pattern. sh-RNA-mediated KRT8 knockdown in these cell lines increases apoptosis, whereas forced overexpression of KRT8 confers resistance to apoptosis under peroxide-induced cell stress conditions. We further show that KRT8 protein binds to annexin A2, a protein known to mediate apoptosis as well as the redox pathway.
PCR Diagnosis of Small Hive Beetles
Authors: Ouessou Idrissou Franck , Huang Qiang , Yañez Orlando , Akinwande Kayode Lawrence , Neumann Peter
Published: February 2018

Small hive beetles (SHBs), Aethina tumida, are parasites of social bee colonies native to sub-Saharan Africa and have become an invasive species at a global scale. Reliable Polymerase Chain Reaction (PCR) diagnosis of this mandatory pest is required to limit its further spread and impact. Here, we have developed SHB primers, which amplify for 10 native African locations and 10 reported introductions, but not for three closely related species (Aethina concolor, Aethina flavicollis, and Aethina inconspicua). We also show that adult honey bee workers can be used as matrices for PCR-based detection of SHBs. The sensitivity of this novel method appears to be 100%, which is identical to conventional visual screenings. Furthermore, the specificity of this novel approach was also high (90.91%). Since both sensitivity and specificity are high, we recommend this novel PCR method and the new primers for routine surveillance of hives in high-risk areas.
Predicting Fatigue Damage of Composites Using Strength Degradation and Cumulative Damage Model
Authors: Khan Arafat , Venkataraman Satchi , Miller Ian
Published: February 2018

This paper discusses the prediction of fatigue response of composites using an empirical strength and stiffness degradation scheme coupled to a cumulative damage accumulation approach. The cumulative damage accumulation approach is needed to account for the non-constant stress levels that arise due to stress distributions from stiffness degradation during the fatigue loading. Degradation of strength and stiffness during fatigue loading of the composite was implemented by following the empirical model presented by Shokrieh and Lessard with some modification and correction to the non-dimensional load parameter definition. The fatigue analysis was performed using ABAQUS™ finite element software using a user-defined material subroutine UMAT developed for the material response. Implementation results were first verified for unidirectional laminate test cases and validated by predicting stress versus life (S-N) curves for several laminate coupons test simulations and residual strengths of Open Hole Tension (OHT) specimens subjected to constant amplitude fatigue loading.
Correction: Thabet, H.; Kendre, S.; Chalishajar, D. New Analytical Technique for Solving a System of Nonlinear Fractional Partial Differential Equations Mathematics 2017, 5, 47
Authors: Thabet Hayman , Kendre Subhash , Chalishajar Dimplekumar
Published: February 2018

We have found some errors in the caption of Figure 1 and Figure 2 in our paper [1], and thus would like to make the following corrections:[...]
A Comparative Study on Asymmetric Reduction of Ketones Using the Growing and Resting Cells of Marine-Derived Fungi
Authors: Liu Hui , Chen Bi-Shuang , De Souza Fayene , Liu Lan
Published: February 2018

Whole-cell biocatalysts offer a highly enantioselective, minimally polluting route to optically active alcohols. Currently, most of the whole-cell catalytic performance involves resting cells rather than growing cell biotransformation, which is one-step process that benefits from the simultaneous growth and biotransformation, eliminating the need for catalysts preparation. In this paper, asymmetric reduction of 14 aromatic ketones to the corresponding enantiomerically pure alcohols was successfully conducted using the growing and resting cells of marine-derived fungi under optimized conditions. Good yields and excellent enantioselectivities were achieved with both methods. Although substrate inhibition might be a limiting factor for growing cell biotransformation, the selected strain can still completely convert 10-mM substrates into the desired products. The resting cell biotransformation showed a capacity to be recycled nine times without a significant decrease in the activity. This is the first study to perform asymmetric reduction of ketones by one-step growing cell biotransformation.
Comparison of Rumen and Manure Microbiomes and Implications for the Inoculation of Anaerobic Digesters
Authors: Ozbayram Emine , Ince Orhan , Ince Bahar , Harms Hauke , Kleinsteuber Sabine
Published: February 2018

Cattle manure is frequently used as an inoculum for the start-up of agricultural biogas plants or as a co-substrate in the anaerobic digestion of lignocellulosic feedstock. Ruminal microbiota are considered to be effective plant fiber degraders, but the microbes contained in manure do not necessarily reflect the rumen microbiome. The aim of this study was to compare the microbial community composition of cow rumen and manure with respect to plant fiber-digesting microbes. Bacterial and methanogenic communities of rumen and manure samples were examined by 454 amplicon sequencing of bacterial 16S rRNA genes and mcrA genes, respectively. Rumen fluid samples were dominated by Prevotellaceae (29%), whereas Ruminococcaceae was the most abundant family in the manure samples (31%). Fibrobacteraceae (12%) and Bacteroidaceae (13%) were the second most abundant families in rumen fluid and manure, respectively. The high abundances of fiber-degrading bacteria belonging to Prevotellaceae and Fibrobacteraceae might explain the better performance of anaerobic digesters inoculated with rumen fluid. Members of the genus Methanobrevibacter were the predominant methanogens in the rumen fluid, whereas methanogenic communities of the manure samples were dominated by the candidate genus Methanoplasma. Our results suggest that inoculation or bioaugmentation with fiber-digesting rumen microbiota can enhance the anaerobic digestion of lignocellulosic biomass.
Effects of an Acute Exercise Bout on Serum Hepcidin Levels
Authors: Domínguez Raúl , Sánchez-Oliver Antonio , Mata-Ordoñez Fernando , Feria-Madueño Adrián , Grimaldi-Puyana Moisés , López-Samanes Álvaro , Pérez-López Alberto
Published: February 2018

Iron deficiency is a frequent and multifactorial disorder in the career of athletes, particularly in females. Exercise-induced disturbances in iron homeostasis produce deleterious effects on performance and adaptation to training; thus, the identification of strategies that restore or maintain iron homeostasis in athletes is required. Hepcidin is a liver-derived hormone that degrades the ferroportin transport channel, thus reducing the ability of macrophages to recycle damaged iron, and decreasing iron availability. Although it has been suggested that the circulating fraction of hepcidin increases during early post-exercise recovery (~3 h), it remains unknown how an acute exercise bout may modify the circulating expression of hepcidin. Therefore, the current review aims to determine the post-exercise expression of serum hepcidin in response to a single session of exercise. The review was carried out in the Dialnet, Elsevier, Medline, Pubmed, Scielo and SPORTDiscus databases, using hepcidin (and “exercise” or “sport” or “physical activity”) as a strategy of search. A total of 19 articles were included in the review after the application of the inclusion/exclusion criteria. This search found that a single session of endurance exercise (intervallic or continuous) at moderate or vigorous intensity (60–90% VO2peak) stimulates an increase in the circulating levels of hepcidin between 0 h and 6 h after the end of the exercise bout, peaking at ~3 h post-exercise. The magnitude of the response of hepcidin to exercise seems to be dependent on the pre-exercise status of iron (ferritin) and inflammation (IL-6). Moreover, oxygen disturbances and the activation of a hypoxia-induced factor during or after exercise may stimulate a reduction of hepcidin expression. Meanwhile, cranberry flavonoids supplementation promotes an anti-oxidant effect that may facilitate the post-exercise expression of hepcidin. Further studies are required to explore the effect of resistance exercise on hepcidin expression.
Rights of Nature: Rivers That Can Stand in Court
Authors: Cano Pecharroman Lidia
Published: February 2018

An increasing number of court rulings and legislation worldwide are recognizing rights of nature to be protected and preserved. Recognizing these rights also entails the recognition that nature has the right to stand in court and to be represented for its defense. This is still an incipient field and every step taken in this direction constitutes a precedent from which to learn and on which to base new rulings and legislation initiatives. Within this doctrine, rivers seem to be on the spotlight and court rulings on the rights of rivers are the ones setting precedent. These cases have taken place in New Zealand, Ecuador, India, and Colombia. This review looks into what all these rulings and legislation worldwide say about the rights of nature and what legal and systemic considerations should be taken into account as the recognition of the rights of nature moves forward.
Artificial Mangrove Species Mapping Using Pléiades-1: An Evaluation of Pixel-Based and Object-Based Classifications with Selected Machine Learning Algorithms
Authors: Wang Dezhi , Wan Bo , Qiu Penghua , Su Yanjun , Guo Qinghua , Wu Xincai
Published: February 2018

In the dwindling natural mangrove today, mangrove reforestation projects are conducted worldwide to prevent further losses. Due to monoculture and the low survival rate of artificial mangroves, it is necessary to pay attention to mapping and monitoring them dynamically. Remote sensing techniques have been widely used to map mangrove forests due to their capacity for large-scale, accurate, efficient, and repetitive monitoring. This study evaluated the capability of a 0.5-m Pléiades-1 in classifying artificial mangrove species using both pixel-based and object-based classification schemes. For comparison, three machine learning algorithms—decision tree (DT), support vector machine (SVM), and random forest (RF)—were used as the classifiers in the pixel-based and object-based classification procedure. The results showed that both the pixel-based and object-based approaches could recognize the major discriminations between the four major artificial mangrove species. However, the object-based method had a better overall accuracy than the pixel-based method on average. For pixel-based image analysis, SVM produced the highest overall accuracy (79.63%); for object-based image analysis, RF could achieve the highest overall accuracy (82.40%), and it was also the best machine learning algorithm for classifying artificial mangroves. The patches produced by object-based image analysis approaches presented a more generalized appearance and could contiguously depict mangrove species communities. When the same machine learning algorithms were compared by McNemar’s test, a statistically significant difference in overall classification accuracy between the pixel-based and object-based classifications only existed in the RF algorithm. Regarding species, monoculture and dominant mangrove species Sonneratia apetala group 1 (SA1) as well as partly mixed and regular shape mangrove species Hibiscus tiliaceus (HT) could well be identified. However, for complex and easily-confused mangrove species Sonneratia apetala group 2 (SA2) and other occasionally presented mangroves species (OT), only major distributions could be extracted, with an accuracy of about two-thirds. This study demonstrated that more than 80% of artificial mangroves species distribution could be mapped.
The Development and Test of a Sensor for Measurement of the Working Level of Gas–Liquid Two-Phase Flow in a Coalbed Methane Wellbore Annulus
Authors: Wu Chuan , Ding Huafeng , Han Lei
Published: February 2018

Coalbed methane (CBM) is one kind of clean-burning gas and has been valued as a new form of energy that will be used widely in the near future. When producing CBM, the working level within a CBM wellbore annulus needs to be monitored to dynamically adjust the gas drainage and extraction processes. However, the existing method of measuring the working level does not meet the needs of accurate adjustment, so we designed a new sensor for this purpose. The principle of our sensor is a liquid pressure formula, i.e., the sensor monitors the two-phase flow patterns and obtains the mean density of the two-phase flow according to the pattern recognition result in the first step, and then combines the pressure data of the working level to calculate the working level using the liquid pressure formula. The sensor was tested in both the lab and on site, and the tests showed that the sensor’s error was ±8% and that the sensor could function well in practical conditions and remain stable in the long term.
Structured Kernel Subspace Learning for Autonomous Robot Navigation
Authors: Kim Eunwoo , Choi Sungjoon , Oh Songhwai
Published: February 2018

This paper considers two important problems for autonomous robot navigation in a dynamic environment, where the goal is to predict pedestrian motion and control a robot with the prediction for safe navigation. While there are several methods for predicting the motion of a pedestrian and controlling a robot to avoid incoming pedestrians, it is still difficult to safely navigate in a dynamic environment due to challenges, such as the varying quality and complexity of training data with unwanted noises. This paper addresses these challenges simultaneously by proposing a robust kernel subspace learning algorithm based on the recent advances in nuclear-norm and l 1 -norm minimization. We model the motion of a pedestrian and the robot controller using Gaussian processes. The proposed method efficiently approximates a kernel matrix used in Gaussian process regression by learning low-rank structured matrix (with symmetric positive semi-definiteness) to find an orthogonal basis, which eliminates the effects of erroneous and inconsistent data. Based on structured kernel subspace learning, we propose a robust motion model and motion controller for safe navigation in dynamic environments. We evaluate the proposed robust kernel learning in various tasks, including regression, motion prediction, and motion control problems, and demonstrate that the proposed learning-based systems are robust against outliers and outperform existing regression and navigation methods.
Multisensor Analysis of Spectral Dimensionality and Soil Diversity in the Great Central Valley of California
Authors: Sousa Daniel , Small Christopher
Published: February 2018

Planned hyperspectral satellite missions and the decreased revisit time of multispectral imaging offer the potential for data fusion to leverage both the spectral resolution of hyperspectral sensors and the temporal resolution of multispectral constellations. Hyperspectral imagery can also be used to better understand fundamental properties of multispectral data. In this analysis, we use five flight lines from the Airborne Visible/Infrared Imaging Spectrometer (AVIRIS) archive with coincident Landsat 8 acquisitions over a spectrally diverse region of California to address the following questions: (1) How much of the spectral dimensionality of hyperspectral data is captured in multispectral data?; (2) Is the characteristic pyramidal structure of the multispectral feature space also present in the low order dimensions of the hyperspectral feature space at comparable spatial scales?; (3) How much variability in rock and soil substrate endmembers (EMs) present in hyperspectral data is captured by multispectral sensors? We find nearly identical partitions of variance, low-order feature space topologies, and EM spectra for hyperspectral and multispectral image composites. The resulting feature spaces and EMs are also very similar to those from previous global multispectral analyses, implying that the fundamental structure of the global feature space is present in our relatively small spatial subset of California. Finally, we find that the multispectral dataset well represents the substrate EM variability present in the study area – despite its inability to resolve narrow band absorptions. We observe a tentative but consistent physical relationship between the gradation of substrate reflectance in the feature space and the gradation of sand versus clay content in the soil classification system.
QLog Solar-Cell Mode Photodiode Logarithmic CMOS Pixel Using Charge Compression and Readout
Authors: Ni Yang
Published: February 2018

In this paper, we present a new logarithmic pixel design currently under development at New Imaging Technologies SA (NIT). This new logarithmic pixel design uses charge domain logarithmic signal compression and charge-transfer-based signal readout. This structure gives a linear response in low light conditions and logarithmic response in high light conditions. The charge transfer readout efficiently suppresses the reset (KTC) noise by using true correlated double sampling (CDS) in low light conditions. In high light conditions, thanks to charge domain logarithmic compression, it has been demonstrated that 3000 electrons should be enough to cover a 120 dB dynamic range with a mobile phone camera-like signal-to-noise ratio (SNR) over the whole dynamic range. This low electron count permits the use of ultra-small floating diffusion capacitance (sub-fF) without charge overflow. The resulting large conversion gain permits a single photon detection capability with a wide dynamic range without a complex sensor/system design. A first prototype sensor with 320 × 240 pixels has been implemented to validate this charge domain logarithmic pixel concept and modeling. The first experimental results validate the logarithmic charge compression theory and the low readout noise due to the charge-transfer-based readout.
A Single RF Emitter-Based Indoor Navigation Method for Autonomous Service Robots
Authors: Sherwin Tyrone , Easte Mikala , Chen Andrew , Wang Kevin , Dai Wenbin
Published: February 2018

Location-aware services are one of the key elements of modern intelligent applications. Numerous real-world applications such as factory automation, indoor delivery, and even search and rescue scenarios require autonomous robots to have the ability to navigate in an unknown environment and reach mobile targets with minimal or no prior infrastructure deployment. This research investigates and proposes a novel approach of dynamic target localisation using a single RF emitter, which will be used as the basis of allowing autonomous robots to navigate towards and reach a target. Through the use of multiple directional antennae, Received Signal Strength (RSS) is compared to determine the most probable direction of the targeted emitter, which is combined with the distance estimates to improve the localisation performance. The accuracy of the position estimate is further improved using a particle filter to mitigate the fluctuating nature of real-time RSS data. Based on the direction information, a motion control algorithm is proposed, using Simultaneous Localisation and Mapping (SLAM) and A* path planning to enable navigation through unknown complex environments. A number of navigation scenarios were developed in the context of factory automation applications to demonstrate and evaluate the functionality and performance of the proposed system.
Mexican-Hat-Like Response in a Flexible Tactile Sensor Using a Magnetorheological Elastomer
Authors: Kawasetsu Takumi , Horii Takato , Ishihara Hisashi , Asada Minoru
Published: February 2018

A significant challenge in robotics is providing a sense of touch to robots. Even though several types of flexible tactile sensors have been proposed, they still have various technical issues such as a large amount of deformation that fractures the sensing elements, a poor maintainability and a deterioration in the sensitivity caused by the presence of a thick and soft covering. As one solution for these issues, we proposed a flexible tactile sensor composed of a magnet, magnetic transducer and dual-layer elastomer, which consists of a magnetorheological and nonmagnetic elastomer sheet. In this study, we first investigated the sensitivity of the sensor, which was found to be high (approximately 161 mV/N with a signal-to-noise ratio of 42.2 dB); however, the sensor has a speed-dependent hysteresis in its sensor response curve. Then, we investigated the spatial response and observed the following results: (1) the sensor response was a distorted Mexican-hat-like bipolar shape, namely a negative response area was observed around the positive response area; (2) the negative response area disappeared when we used a compressible sponge sheet instead of the incompressible nonmagnetic elastomer. We concluded that the characteristic negative response in the Mexican-hat-like response is derived from the incompressibility of the nonmagnetic elastomer.
A Novel Strategy for Very-Large-Scale Cash-Crop Mapping in the Context of Weather-Related Risk Assessment, Combining Global Satellite Multispectral Datasets, Environmental Constraints, and In Situ Acquisition of Geospatial Data
Authors: Dell’Acqua Fabio , Iannelli Gianni , Torres Marco , Martina Mario
Published: February 2018

Cash crops are agricultural crops intended to be sold for profit as opposed to subsistence crops, meant to support the producer, or to support livestock. Since cash crops are intended for future sale, they translate into large financial value when considered on a wide geographical scale, so their production directly involves financial risk. At a national level, extreme weather events including destructive rain or hail, as well as drought, can have a significant impact on the overall economic balance. It is thus important to map such crops in order to set up insurance and mitigation strategies. Using locally generated data—such as municipality-level records of crop seeding—for mapping purposes implies facing a series of issues like data availability, quality, homogeneity, etc. We thus opted for a different approach relying on global datasets. Global datasets ensure homogeneity and availability of data, although sometimes at the expense of precision and accuracy. A typical global approach makes use of spaceborne remote sensing, for which different land cover classification strategies are available in literature at different levels of cost and accuracy. We selected the optimal strategy in the perspective of a global processing chain. Thanks to a specifically developed strategy for fusing unsupervised classification results with environmental constraints and other geospatial inputs including ground-based data, we managed to obtain good classification results despite the constraints placed. The overall production process was composed using “good-enough" algorithms at each step, ensuring that the precision, accuracy, and data-hunger of each algorithm was commensurate to the precision, accuracy, and amount of data available. This paper describes the tailored strategy developed on the occasion as a cooperation among different groups with diverse backgrounds, a strategy which is believed to be profitably reusable in other, similar contexts. The paper presents the problem, the constraints and the adopted solutions; it then summarizes the main findings including that efforts and costs can be saved on the side of Earth Observation data processing when additional ground-based data are available to support the mapping task.