bluuebunny/crossref_metadata_2025 huggingface dataset:
Quality Evaluation of Mahonia bealei (Fort.) Carr. Using Supercritical Fluid Chromatography with Chemical Pattern Recognition
Authors: Huang Yang , Jiang Zhengjin , Wang Jue , Yin Guo , Jiang Kun , Tu Jiasheng , Wang Tiejie
Published: October 2019

Mahonia bealei (Fort.) Carr. (M. bealei) plays an important role in the treatment of many diseases. In the present study, a comprehensive method combining supercritical fluid chromatography (SFC) fingerprints and chemical pattern recognition (CPR) for quality evaluation of M. bealei was developed. Similarity analysis, hierarchical cluster analysis (HCA), principal component analysis (PCA) were applied to classify and evaluate the samples of wild M. bealei, cultivated M. bealei and its substitutes according to the peak area of 11 components but an accurate classification could not be achieved. PLS-DA was then adopted to select the characteristic variables based on variable importance in projection (VIP) values that responsible for accurate classification. Six characteristics peaks with higher VIP values (≥1) were selected for building the CPR model. Based on the six variables, three types of samples were accurately classified into three related clusters. The model was further validated by a testing set samples and predication set samples. The results indicated the model was successfully established and predictive ability was also verified satisfactory. The established model demonstrated that the developed SFC coupled with PLS-DA method showed a great potential application for quality assessment of M. bealei.
Advances in the Interpretation of Frequency-Dependent Nuclear Magnetic Resonance Measurements from Porous Material
Authors: Faux David , Kogon Rémi , Bortolotti Villiam , McDonald Peter
Published: October 2019

Fast-field-cycling nuclear magnetic resonance (FFC-NMR) is a powerful technique for non-destructively probing the properties of fluids contained within the pores of porous materials. FFC-NMR measures the spin–lattice relaxation rate R 1 ( f ) as a function of NMR frequency f over the kHz to MHz range. The shape and magnitude of the R 1 ( f ) dispersion curve is exquisitely sensitive to the relative motion of pairs of spins over time scales of picoseconds to microseconds. To extract information on the nano-scale dynamics of spins, it is necessary to identify a model that describes the relative motion of pairs of spins, to translate the model dynamics to a prediction of R 1 ( f ) and then to fit to the experimental dispersion. The principles underpinning one such model, the 3 τ model, are described here. We present a new fitting package using the 3 τ model, called 3TM, that allows users to achieve excellent fits to experimental relaxation rates over the full frequency range to yield five material properties and much additional derived information. 3TM is demonstrated on historic data for mortar and plaster paste samples.
Investigating Immersion and Learning in a Low-Embodied versus High-Embodied Digital Educational Game: Lessons Learned from an Implementation in an Authentic School Classroom
Authors: Georgiou Yiannis , Ioannou Andri , Ioannou Marianna
Published: October 2019

Immersion is often argued to be one of the main driving forces behind children’s learning in digital educational games. Researchers have supported that movement-based interaction afforded by emerging embodied digital educational games may heighten even more immersion and learning. However, there is lack of empirical research warranting these claims. This case study has investigated the impact of high-embodied digital educational game, integrated in a primary school classroom, on children’s immersion and content knowledge about nutrition (condition1 = 24 children), in comparison to the impact of a low-embodied version of the game (condition2 = 20 children). Post-interventional surveys investigating immersion indicated that there was difference only on the level of engagement, in terms of perceived usability, while children’s learning gains in terms of content knowledge did not differ among the two conditions. Interviews with a subset of the children (n = 8 per condition) resulted in the identification of (a) media form, (b) media content and (c) context-related factors, which provided plausible explanations about children’s experienced immersion. Implications are discussed for supporting immersion in high-embodied educational digital games.
Hydrothermal Fabrication of Spindle-Shaped ZnO/Palygorskite Nanocomposites Using Nonionic Surfactant for Enhancement of Antibacterial Activity
Authors: Hui Aiping , Dong Shuqing , Kang Yuru , Zhou Yanmin , Wang Aiqin
Published: October 2019

In order to improve the antibacterial performance of natural palygorskite, spindle-like ZnO/palygorskite (ZnO/PAL) nanocomposites with controllable growth of ZnO on the surface of PAL were prepared in the presence of non-ionic surfactants using an easy-to-operate hydrothermal method. The obtained ZnO/PAL nanocomposites have a novel and special spindle-shaped structure and good antibacterial activity against Escherichia coli (E. coli) and Staphylococcus aureus (S. aureus), and are also low cost. The minimum inhibitory concentrations of ZnO/PAL nanocomposites toward E. coli and S. aureus reached 1.5 and 5 mg/mL, respectively.
Observational Study on Knowledge and Eating Habits with Respect to Low- and High-FODMAP Foods in Medical Checkup Populations in Japan
Authors: Kaneko Hiroshi , Tsuboi Hirohito , Yamamoto Sayuri , Konagaya Toshihiro
Published: October 2019

Background: There has been an increasing interest in low fermentable oligosaccharides, disaccharides, monosaccharides, and polyols (FODMAP) diets for irritable bowel syndrome. The aims of the present study were (1) to survey knowledge and eating habits with respect to low- and high-FODMAP foods in a general population, and (2) to analyze the relationship between lower gastrointestinal problems (LGIP, pain and irregular stool habits) and habits/foods for prevention. Methods: The present study was carried out with medical examinees (n = 1024) at a clinic in Japan using self-administrated questionnaires. The subjects were asked whether they knew each FODMAP food, eating habit, and cooking habit. Chi-squared tests were used for analyzing the characteristics of LGIP-related factors. Logistic regression models were utilized to select foods which predict LGIP. Results: Women cooking by themselves and who were younger indicated less LGIP (Chai-square for trend). More than 60% reported that they often ate rice, coffee, eggs, pork, chicken, breads, noodles, and onions, which are solely classified as high-FODMAP foods. LGIP was related to age and self-cooking habits in women. Soybeans had the least significant relationship with LGIP (odds ratio (OR) 0.48, 95% confidence interval (CI) 0.32–0.73), followed by seaweed, shellfish, wheat, cow’s milk, green beans, and cauliflower. In contrast, artificial sweeteners were most significantly related with LGIP (OR 1.54, 95% CI 1.16–2.03), followed by margarine and tomato paste. Conclusions: The associations between FODMAP foods and LGPI appeared to be different from the Western results. Furthermore, some diets related to LGIP are suggested.
‘Oh God, I Have to Eat Something, But Where Can I Get Something Quickly?’—A Qualitative Interview Study on Barriers to Healthy Eating among University Students in Germany
Authors: Hilger-Kolb Jennifer , Diehl Katharina
Published: October 2019

Healthy eating can prevent individuals across all age groups from developing overweight/obesity and non-communicable diseases such as type 2 diabetes and cardiovascular disease. However, unhealthy eating habits (e.g., a high level of fast food consumption) have been found to be widespread among university students. Thus, it seems necessary to develop prevention strategies to improve students’ eating habits. However, to ensure that such strategies are successful, it is important that they fit the needs of the target population. By conducting qualitative interviews with students (n = 20), we aimed to get a deeper understanding of barriers to healthy eating. Students were asked about barriers to healthy eating and to suggest possible ideas that could improve their eating behavior in the future. Our findings revealed that students are especially affected by time-related barriers (e.g., a lack of time due to university commitment) and environmental barriers (e.g., a lack of cheap, tasty, and healthy meal options at the university canteen). Time-related barriers were also related to motivational barriers (e.g., being too lazy to cook after a busy day at university). In addition, knowledge/information-related barriers, social-support-related barriers, and transition-related barriers emerged from our interviews. The variety of barriers addressed and the different views on some of these, indicate that various strategies seem to be needed to improve the eating behavior among university students and to prevent them from gaining weight and developing non-communicable diseases in the future.
Extra-Virgin Olive Oil Modifies the Changes Induced in Non-Nervous Organs and Tissues by Experimental Autoimmune Encephalomyelitis Models
Authors: Conde Cristina , Escribano Begoña M. , Luque Evelio , Feijóo Montserrat , Caballero-Villarraso Javier , Valdelvira Manuel E. , Ochoa-Sepúlveda Juan J. , Lillo Rafael , Paz Elier , Santamaría Abel , Agüera Eduardo , Túnez Isaac
Published: October 2019

This study reveals the existence of oxidative stress (reactive oxygen species (ROS)) in non-nervous organs and tissues in multiple sclerosis (MS) by means of a model of experimental autoimmune encephalomyelitis (EAE) in rats. This model reproduces a similar situation to MS, as well as its relationship with intestinal microbiota starting from the changes in bacterial lipopolysaccharide levels (LPS) in the outer wall of the gram-negative bacteria. Finally, the administration of extra-virgin olive oil (EVOO), hydroxytirosol (HT), and oleic acid (OA) exert beneficial effects. Twenty-five Dark Agouti two-month-old male rats, weighing around 190 g, were distributed into the following groups: Control, EAE (experimental autoimmune encephalomyelitis group), EAE + EVOO, EAE + HT, and EAE + OA. The glutathione redox system with the EAE was measured in heart, kidney, liver, and small and large intestines. The LPS and the correlation with oxidative stress in the small and large intestines were also investigated. The results showed that (1) the oxidative damage in the EAE model affects non-nervous organs and tissues; (2) The LPS is related to inflammatory phenomena and oxidative stress in the intestinal tissue and in other organs; (3) The administration of EVOO, HT, and OA reduces the LPS levels at the same time as minimizing the oxidative damage; (4) EVOO, HT, and OA improve the disease’s clinical score; and (5) on balance, EVOO offers a better neuroprotective effect.
Effect of Probiotics on Oral Candidiasis: A Systematic Review and Meta-Analysis
Authors: Mundula Tiziana , Ricci Federica , Barbetta Beatrice , Baccini Michela , Amedei Amedeo
Published: October 2019

Oral candidiasis (OC) is an increasing health problem due to the introduction of new drugs, population aging, and increasing prevalence of chronic illness. This study systematically reviews the effects of the oral intake of probiotics, prebiotics, and synbiotics on Candida spp. counts (colony-forming units (CFU)/mL) in oral and palatal samples. A literature search was conducted. Twelve studies, eight randomized clinical trials (RCTs), and four pre-post studies, resulted as eligible for the meta-analysis, which was performed through a Bayesian random-effects model. All studies analyzed probiotics, and none of them analyzed prebiotics or synbiotics. The treatments effects were measured in terms of odds ratio (OR) of OC (CFU/mL >102, 103, or 104). The meta-analytic OR was 0.71 (95% credibility interval (CrI): 0.37, 1.32), indicating a beneficial effect of treatment; the I2 index was 56.3%. Focusing only on RCTs, the OR was larger and more precise at 0.53 (95% CrI: 0.27, 0.93). The effect of treatment appeared to be larger on denture wearers. Our findings indicate that the intake of probiotics can have a beneficial effect on OC and that the effects could vary according to the patients’ characteristics. Due to the presence of medium–high-risk studies, the results should be interpreted with caution.
A Review of the Potential Benefits of Increasing Vitamin D Status in Mongolian Adults through Food Fortification and Vitamin D Supplementation
Authors: Grant William B. , Boucher Barbara J.
Published: October 2019

Serum 25-hydroxyvitamin D (25(OH)D) concentrations are low in Mongolia, averaging 22 ng/mL in summer and only 8 ng/mL in winter. Mongolians have high incidence and/or prevalence of several diseases linked to low 25(OH)D concentrations, including ischemic heart disease, malignant neoplasms, cirrhosis of the liver, ischemic stroke, lower respiratory tract infections, preterm birth complications, and diabetes mellitus. Fortifying regularly consumed foods such as flour, milk, and edible oils with vitamin D3 could raise 25(OH)D concentrations by about 10 ng/mL. However, to achieve 25(OH)D concentrations of 30–40 ng/mL in adults, vitamin D intakes of 1000 to 4000 IU/day would be required, making personal supplement use necessary. On the basis of prospective observational studies and clinical trials of disease incidence or known mortality rates and adverse pregnancy and birth outcomes, raising mean serum 25(OH)D concentrations to 40 ng/mL would likely reduce incidence and mortality rates for those and other diseases, reduce the rate of adverse pregnancy and birth outcomes, and increase mean life expectancy by one year or more.
Inactivation of Zika Virus by Photoactive Iodonaphthyl Azide Preserves Immunogenic Potential of the Virus
Authors: Austin Amy L. , Galasso Bianca , Nickens Caitlin , Knollmann-Ritschel Barbara , Sharma Anuj
Published: October 2019

Zika virus’s (ZIKV) emergence as a pathogen of significant public health importance has accelerated efforts to develop a ZIKV vaccine. To date, the need for an effective ZIKV vaccine is unmet. In this study, we report inactivation of ZIKV using a hydrophobic photoactive compound: 1, 5 iodonaphthyl azide (INA). 50 and 100 µM of INA completely inactivated ZIKV (INA-ZIKV). Western blot and ELISA analysis show some loss of the binding capacity of INA-iZIKV to anti-ZIKV monoclonal antibodies; however, immunization of mice with INA-iZIKV demonstrated seroconversion and ZIKV-neutralizing antibody response. RNA isolated from INA-iZIKV did not induce productive infection in Vero cells, suggesting inactivation of ZIKV RNA. These results suggest that in the absence of an approved ZIKV vaccine, INA-iZIKV can be pursued as a viable ZIKV vaccine candidate.
A Combinatorial Cell and Drug Delivery Strategy for Huntington’s Disease Using Pharmacologically Active Microcarriers and RNAi Neuronally-Committed Mesenchymal Stromal Cells
Authors: André Emilie M. , Delcroix Gaëtan J. , Kandalam Saikrishna , Sindji Laurence , Montero-Menei Claudia N.
Published: October 2019

For Huntington’s disease (HD) cell-based therapy, the transplanted cells are required to be committed to a neuronal cell lineage, survive and maintain this phenotype to ensure their safe transplantation in the brain. We first investigated the role of RE-1 silencing transcription factor (REST) inhibition using siRNA in the GABAergic differentiation of marrow-isolated adult multilineage inducible (MIAMI) cells, a subpopulation of MSCs. We further combined these cells to laminin-coated poly(lactic-co-glycolic acid) PLGA pharmacologically active microcarriers (PAMs) delivering BDNF in a controlled fashion to stimulate the survival and maintain the differentiation of the cells. The PAMs/cells complexes were then transplanted in an ex vivo model of HD. Using Sonic Hedgehog (SHH) and siREST, we obtained GABAergic progenitors/neuronal-like cells, which were able to secrete HGF, SDF1 VEGFa and BDNF, of importance for HD. GABA-like progenitors adhered to PAMs increased their mRNA expression of NGF/VEGFa as well as their secretion of PIGF-1, which can enhance reparative angiogenesis. In our ex vivo model of HD, they were successfully transplanted while attached to PAMs and were able to survive and maintain this GABAergic neuronal phenotype. Together, our results may pave the way for future research that could improve the success of cell-based therapy for HDs.
Population Pharmacokinetics of Cis-, Trans-, and Total Cefprozil in Healthy Male Koreans
Authors: Jang Ji-Hun , Jeong Seung-Hyun , Cho Hea-Young , Lee Yong-Bok
Published: October 2019

Cefprozil, one of cephalosporin antibiotics, has been used extensively in clinics. However, pharmacokinetic (PK) information on cefprozil is still very limited. There have been no reports of population pharmacokinetics (PPKs). A PPK model for cefprozil will be a great advantage for clinical use. Thus, the aim of this study was to develop a PPK model for cefprozil for healthy male Koreans. Clinical PK and demographic data of healthy Korean males receiving cefprozil at a dose of 1000 mg were analyzed using Phoenix® NLME™. A one-compartment model with first-order absorption with lag-time was constructed as a base model. The model was extended to include covariates that influenced between-subject variability. Creatinine clearance significantly influenced systemic clearance of cefprozil. The final PPK model for cis-, trans-, and total cefprozil was established and validated. PPK parameter values of cis- and total cefprozil were similar to each other, but different from those of trans-isomer. Herein, we describe the establishment of accurate PPK models of cis-, trans-, and total cefprozil for healthy male Koreans for the first time. It may be useful as a dosing algorithm for the general population. These results might also contribute to the development of stereoisomeric cefprozil.
Irregular Shifting of RF Driving Signal Phase to Overcome Dispersion Power Fading
Authors: Ujang Febrizal , Firmansyah Teguh , Priambodo Purnomo S. , Wibisono Gunawan
Published: October 2019

The main problem with the radio-over-fiber (RoF) link is the decrease in the recovered radio frequency (RF) power due to the chromatic dispersion of the fiber known as dispersion power fading. One of the methods for dealing with dispersion power fading is to use the optical single sideband (OSSB) modulation scheme. The OSSB modulation scheme can be generated by biasing the dual-drive Mach–Zehnder modulator (DD-MZM) to the quadrature bias point (QBP) and shifting the RF drive signal phase (θ) by 90°, which is called the regular θ. However, the OSSB modulation scheme only overcomes dispersion power fading well at the modulation index (m) < 0.2. This paper proposes an irregular θ method to overcome dispersion power fading at all m. There are two irregular θ for every m used. The irregular θ managed to handle dispersion power fading better than OSSB modulation scheme did at every m. Specifically, the irregular θ could handle the dispersion power fading well at m ≤ 1. In sum, the irregular θ could overcome the dispersion power fading at any RF frequency and optical wavelength without having to re-adjust the transmitter.
Leaf Production and Expansion: A Generalized Response to Drought Stresses from Cells to Whole Leaf Biomass—A Case Study in the Tomato Compound Leaf
Authors: Koch Garance , Rolland Gaëlle , Dauzat Myriam , Bédiée Alexis , Baldazzi Valentina , Bertin Nadia , Guédon Yann , Granier Christine
Published: October 2019

It is clearly established that there is not a unique response to soil water deficit but that there are as many responses as soil water deficit characteristics: Drought intensity, drought duration, and drought position during plant cycle. For a same soil water deficit, responses can also differ on plant genotype within a same species. In spite of this variability, at least for leaf production and expansion processes, robust tendencies can be extracted from the literature when similar watering regimes are compared. Here, we present response curves and multi-scale dynamics analyses established on tomato plants exposed to different soil water deficit treatments. Results reinforce the trends already observed for other species: Reduction in plant leaf biomass under water stress was due to reduction in individual leaf biomass and areas whereas leaf production and specific leaf area were not affected. The dynamics of leaf expansion was modified both at the leaf and cell scales. Cell division and expansion were reduced by drought treatments as well as the endoreduplication process. Combining response curves analyses together with dynamic analyses of tomato compound leaf growth at different scales not only corroborate results on simple leaf responses to drought but also increases our knowledge on the cellular mechanisms behind leaf growth plasticity.
Antimicrobial Activity and Mechanism of Functionalized Quantum Dots
Authors: Rajendiran Keerthiga , Zhao Zizhen , Pei De-Sheng , Fu Ailing
Published: October 2019

An essential characteristic of quantum dots (QDs) is their antimicrobial activity. Compared with conventional antibiotics, QDs not only possess photoluminescence properties for imaging and photodynamic therapy but also have high structural stability. To enhance their antimicrobial efficiency, QDs usually are functionalized by polymers, including poly(ethylene glycol), polyethyleneimine, and poly-l-lysine. Also, QDs conjugated with polymers, such as poly(vinylpyrrolidone) and polyvinylidene fluoride, are prepared as antimicrobial membranes. The main antimicrobial mechanisms of QDs are associated with inducing free radicals, disrupting cell walls/membranes, and arresting gene expression. The different mechanisms from traditional antibiotics allow QDs to play antimicrobial roles in multi-drug-resistant bacteria and fungi. Since the toxicity of the QDs on animal cells is relatively low, they have broad application in antimicrobial research as an effective alternative of traditional antibiotics.
Potato Starch Hydrogels Produced by High Hydrostatic Pressure (HHP): A First Approach
Authors: Larrea-Wachtendorff Dominique , Tabilo-Munizaga Gipsy , Ferrari Giovanna
Published: October 2019

Starch-based hydrogels have received considerable interest due to their safe nature, biodegradability and biocompatibility. The aim of this study was to verify the possibility of producing natural hydrogels based on potato starch by high hydrostatic pressure (HHP), identifying suitable processing conditions allowing to obtain stable hydrogels, as well as to characterize structural and mechanical properties of these products. Sieved (small size granules and medium size granules) and unsieved potato starch samples were used to prepare aqueous suspensions of different concentrations (10–30% w/w) which were processed at 600 MPa for 15 min at different temperatures (25, 40 and 50 °C). Products obtained were characterized by different techniques (light and polarized microscopy, Fourier transform infrared spectroscopy (FTIR), rheology and differential scanning calorimetry (DSC)). Results obtained so far demonstrated that potato starch suspensions (20% starch–water concentration (w/w)) with granules mean size smaller than 25 µm treated at 600 MPa for 15 min and 50 °C showed a complete gelatinization and gel-like appearance. Potato HHP hydrogels were characterized by high viscosity, shear-thinning behavior and a highly structured profile (G’ >> G’’). Moreover, their FTIR spectra, similarly to FTIR profiles of thermal gels, presented three absorption bands in the characteristic starch-gel region (950–1200 cm−1), whose intensity increased with decreasing the particle size and increasing the processing temperature. In conclusion, potato starch hydrogels produced by HHP in well-defined processing conditions exhibited excellent mechanical properties, which can be tailored according to the requirements of the different applications envisaged.
Photothermal Responsive Porous Membrane for Treatment of Infected Wound
Authors: Phan Thi Tuong Vy , Huynh Thanh-Canh , Oh Junghwan
Published: October 2019

Wound infection is a big issue of modern medicine because of multi-drug resistance bacteria; thus, developing an advanced therapy is curial. Photothermal therapy (PTT) is a newly noninvasive strategy that employs PTT agents to transfer near-infrared (NIR) light energy into heat to kill bacterial pathogens. In this work, the PTT agent-containing dressing was developed for the first time to treat the wound infection. Palladium nanoparticles (PdNPs) were chosen as PTT agents because of their high stability, good biocompatibility, excellent photothermal property, and simple-green preparation. With the flexibility and wettability, highly porous membrane chitosan/polyvinyl alcohol (CS/PVA) membrane was chosen as the dressing. The prepared wound dressings exhibited excellent biocompatibility, high porosity, a high degree of swelling, high moisture retention, and high photothermal performance. The treatment of PdNPs loading CS/PVA dressing (CS/PVA/Pd) and laser irradiation killed most of the bacteria in vitro. The proposed PTT agent containing wound dressing introduces a novel strategy for the treatment of wound infection.
Neural-Network-Based Building Energy Consumption Prediction with Training Data Generation
Authors: Lee Sanghyuk , Cha Jaehoon , Kim Moon Keun , Kim Kyeong Soo , Pham Van Huy , Leach Mark
Published: October 2019

The importance of neural network (NN) modelling is evident from its performance benefits in a myriad of applications, where, unlike conventional techniques, NN modeling provides superior performance without relying on complex filtering and/or time-consuming parameter tuning specific to applications and their wider ranges of conditions. In this paper, we employ NN modelling with training data generation based on sensitivity analysis for the prediction of building energy consumption to improve performance and reliability. Unlike our previous work, where insignificant input variables are successively screened out based on their mean impact values (MIVs) during the training process, we use the receiver operating characteristic (ROC) plot to generate reliable data with a conservative or progressive point of view, which overcomes the issue of data insufficiency of the MIV method: By properly setting boundaries for input variables based on the ROC plot and their statistics, instead of completely screening them out as in the MIV-based method, we can generate new training data that maximize true positive and false negative numbers from the partial data set. Then a NN model is constructed and trained with the generated training data using Levenberg–Marquardt back propagation (LM-BP) to perform electricity prediction for commercial buildings. The performance of the proposed data generation methods is compared with that of the MIV method through experiments, whose results show that data generation using successive and cross pattern provides satisfactory performance, following energy consumption trends with good phase. Among the two options in data generation, i.e., successive and two data combination, the successive option shows lower root mean square error (RMSE) than the combination one by around 400~900 kWh (i.e., 30%~75%).
Activation Energy Determination in Case of Independent Complex Kinetic Processes
Authors: Luciano Giorgio , Svoboda Roman
Published: October 2019

Theoretically simulated kinetic data were used to evaluate the performance of the most common isoconversional methods of kinetic analysis in complex-process scenarios with two independent overlapping processes exhibiting nucleation-growth kinetics, and further expand the conclusions for the autocatalytic kinetic processes with positive asymmetry. In close-to-real-life situations all the integral isoconversional methods provided practically indistinguishable E-α outcomes. The Friedman and incremental modified Vyazovkin methods results in significant over- and undershoots. However, the combined utilization of the integral and differential isoconversional methods was demonstrated to greatly contribute to the interpretation of the E-α dependences and estimation of E1 and E2—the conceptual evaluation involving positions of inflection points and plateaus is introduced. The influence of the range of applied heating rates q+ on the course of E-α dependences was studied. In this regard, the performance of the isoconversional methods changes significantly with both, the consistence of the shape of the complex kinetic curve and weighted presence of full overlaps of the involved sub-processes.
Fatwas on Boosting Environmental Conservation in Indonesia
Authors: Mangunjaya Fachruddin Majeri , Praharawati Gugah
Published: October 2019

Concern about the importance of getting Muslims involved in the movement for a better environment in Indonesia has existed since the 1980s, since the involvement of the Islamic boarding school leaders in triggering their community and the involvement of NGOs in empowering the community, particularly in environmental and agricultural restoration. After the Bogor Declaration on Muslim Action on Climate Change 2010, in 2011, The Indonesia Council of Ulama (MUI) established the Institute for Environmental and Natural Resources (PLHSDA) in the MUI’s Clerical Conference. The role of this unit within the MUI is very important because the MUI has a special unit in tackling various important issues in the environment, where Muslims can find authoritative answers to environmental challenges. So far, there have been seven MUI fatāwa (edicts) released by MUI related to the environment and the conservation movement. This paper will highlight environmental movements by the Muslim community in Indonesia, and describe how the implementation of the MUI fatāwa can contribute to addressing the massive increase in environmental challenges and increase the involvement and understanding of the Muslim communities in tackling biodiversity conservation as well as climate change.
In Search of Sylhet—The Fultoli Tradition in Britain
Authors: Ahmed Abdul-Azim , Ali Mansur
Published: October 2019

This article presents a case study of the Fultoli tradition, an expression of Islam dominant amongst Bangladeshi migrants to the UK, but which in general terms has failed to communicate itself to British-born Muslims. It is also a denominational identity that has been overlooked in academic literature on British Muslims, and regularly mischaracterized. To correct this, the article presents an overview of Fultolir Sahib, the late founder of the tradition, and the theological distinctiveness of his teachings, before considering its movement to Britain. A varied methodological approach is adopted in order to explore the topic, combining a textual exploration of Fultoli sources with qualitative interviews with members of the Fultoli tradition, and also autoethnography drawing upon the authors’ (who were both raised by Fultoli parents) experience of the tradition. The article argues that Fultolir Sahib’s authority is constructed in an idiom that is inaccessible to British-born Muslims and that Fultoli institutions have failed to create leaders capable of preserving the tradition. It concludes that despite the diminishing numbers of Fultolis in Britain, it is still important for academics to recognize their unique role in the landscape of Muslim denominational diversity.
Claim Watching and Individual Claims Reserving Using Classification and Regression Trees
Authors: De Felice Massimo , Moriconi Franco
Published: October 2019

We present an approach to individual claims reserving and claim watching in general insurance based on classification and regression trees (CART). We propose a compound model consisting of a frequency section, for the prediction of events concerning reported claims, and a severity section, for the prediction of paid and reserved amounts. The formal structure of the model is based on a set of probabilistic assumptions which allow the provision of sound statistical meaning to the results provided by the CART algorithms. The multiperiod predictions required for claims reserving estimations are obtained by compounding one-period predictions through a simulation procedure. The resulting dynamic model allows the joint modeling of the case reserves, which usually yields useful predictive information. The model also allows predictions under a double-claim regime, i.e., when two different types of compensation can be required by the same claim. Several explicit numerical examples are provided using motor insurance data. For a large claims portfolio we derive an aggregate reserve estimate obtained as the sum of individual reserve estimates and we compare the result with the classical chain-ladder estimate. Backtesting exercises are also proposed concerning event predictions and claim-reserve estimates.
Ocean Response to Successive Typhoons Sarika and Haima (2016) Based on Data Acquired via Multiple Satellites and Moored Array
Authors: Zhang Han , Liu Xiaohui , Wu Renhao , Liu Fu , Yu Linghui , Shang Xiaodong , Qi Yongfeng , Wang Yuan , Song Xunshu , Xie Xiaohui , Yang Chenghao , Tian Di , Zhang Wenyan
Published: October 2019

Tropical cyclones (TCs) are natural disasters for coastal regions. TCs with maximum wind speeds higher than 32.7 m/s in the north-western Pacific are referred to as typhoons. Typhoons Sarika and Haima successively passed our moored observation array in the northern South China Sea in 2016. Based on the satellite data, the winds (clouds and rainfall) biased to the right (left) sides of the typhoon tracks. Sarika and Haima cooled the sea surface ~4 and ~2 °C and increased the salinity ~1.2 and ~0.6 psu, respectively. The maximum sea surface cooling occurred nearly one day after the two typhoons. Station 2 (S2) was on left side of Sarika’s track and right side of Haima’s track, which is studied because its data was complete. Strong near-inertial currents from the ocean surface toward the bottom were generated at S2, with a maximum mixed-layer speed of ~80 cm/s. The current spectrum also shows weak signal at twice the inertial frequency (2f). Sarika deepened the mixed layer, cooled the sea surface, but warmed the subsurface by ~1 °C. Haima subsequently pushed the subsurface warming anomaly into deeper ocean, causing a temperature increase of ~1.8 °C therein. Sarika and Haima successively increased the heat content anomaly upper than 160 m at S2 to ~50 and ~100 m°C, respectively. Model simulation of the two typhoons shows that mixing and horizontal advection caused surface ocean cooling, mixing and downwelling caused subsurface warming, while downwelling warmed the deeper ocean. It indicates that Sarika and Haima sequentially modulated warm water into deeper ocean and influenced internal ocean heat budget. Upper ocean salinity response was similar to temperature, except that rainfall refreshed sea surface and caused a successive salinity decrease of ~0.03 and ~0.1 psu during the two typhoons, changing the positive subsurface salinity anomaly to negative
A hybrid OSVM-OCNN Method for Crop Classification from Fine Spatial Resolution Remotely Sensed Imagery
Authors: Li Huapeng , Zhang Ce , Zhang Shuqing , Atkinson Peter M.
Published: October 2019

Accurate information on crop distribution is of great importance for a range of applications including crop yield estimation, greenhouse gas emission measurement and management policy formulation. Fine spatial resolution (FSR) remotely sensed imagery provides new opportunities for crop mapping at a detailed level. However, crop classification from FSR imagery is known to be challenging due to the great intra-class variability and low inter-class disparity in the data. In this research, a novel hybrid method (OSVM-OCNN) was proposed for crop classification from FSR imagery, which combines a shallow-structured object-based support vector machine (OSVM) with a deep-structured object-based convolutional neural network (OCNN). Unlike pixel-wise classification methods, the OSVM-OCNN method operates on objects as the basic units of analysis and, thus, classifies remotely sensed images at the object level. The proposed OSVM-OCNN harvests the complementary characteristics of the two sub-models, the OSVM with effective extraction of low-level within-object features and the OCNN with capture and utilization of high-level between-object information. By using a rule-based fusion strategy based primarily on the OCNN’s prediction probability, the two sub-models were fused in a concise and effective manner. We investigated the effectiveness of the proposed method over two test sites (i.e., S1 and S2) that have distinctive and heterogeneous patterns of different crops in the Sacramento Valley, California, using FSR Synthetic Aperture Radar (SAR) and FSR multispectral data, respectively. Experimental results illustrated that the new proposed OSVM-OCNN approach increased markedly the classification accuracy for most of crop types in S1 and all crop types in S2, and it consistently achieved the most accurate accuracy in comparison with its two object-based sub-models (OSVM and OCNN) as well as the pixel-wise SVM (PSVM) and CNN (PCNN) methods. Our findings, thus, suggest that the proposed method is as an effective and efficient approach to solve the challenging problem of crop classification using FSR imagery (including from different remotely sensed platforms). More importantly, the OSVM-OCNN method is readily generalisable to other landscape classes and, thus, should provide a general solution to solve the complex FSR image classification problem.
Neural Image Analysis and Electron Microscopy to Detect and Describe Selected Quality Factors of Fruit and Vegetable Spray-Dried Powders—Case Study: Chokeberry Powder
Authors: Przybył Krzysztof , Gawałek Jolanta , Koszela Krzysztof , Przybył Jacek , Rudzińska Magdalena , Gierz Łukasz , Domian Ewa
Published: October 2019

The study concentrates on researching possibilities of using computer image analysis and neural modeling in order to assess selected quality discriminants of spray-dried chokeberry powder. The aim of the paper is the quality identification of chokeberry powders on account of their highest dying power, the highest bioactivity, as well as technologically satisfying looseness of the powder. The article presents neural models with vision techniques backed up by devices such as digital cameras, as well as an electron microscope. The reduction in size of input variables with PCA has an influence on improving the processes of learning data sets, thus increasing the effectiveness of identifying chokeberry fruit powders included in digital pictures, which is shown in the results of the conducted research. The effectiveness of image recognition is presented by classifying abilities, as well as low Root Mean Square Error (RMSE), for which the best results are achieved with a typology of network type Multi-Layer Perceptron (MLP). The selected networks type MLP are characterized by the highest degree of classification at 0.99 and RMSE at 0.11 at most at the same time.
Field Research Cooperative Wearable Systems: Challenges in Requirements, Design and Validation
Authors: Silva Mateus C. , Amorim Vicente J. P. , Ribeiro Sérvio P. , Oliveira Ricardo A. R.
Published: October 2019

The widespread availability of wearable devices is evolving them into cooperative systems. Communication and distribution aspects such as the Internet of Things, Wireless Body Area Networks, and Local Wireless Networks provide the means to develop multi-device platforms. Nevertheless, the field research environment presents a specific feature set, which increases the difficulty in the adoption of this technology. In this text, we review the main aspects of Field Research Gears and Wearable Devices. This review is made aiming to understand how to create cooperative systems based on wearable devices directed to the Field Research Context. For a better understanding, we developed a case study in which we propose a cooperative system architecture and provide validation aspects. For this matter, we provide an overview of a previous device architecture and study an integration proposal.
Harvest Stage Recognition and Potential Fruit Damage Indicator for Berries Based on Hidden Markov Models and the Viterbi Algorithm
Authors: Orchard Marcos , Muñoz-Poblete Carlos , Huircan Juan Ignacio , Galeas Patricio , Rozas Heraldo
Published: October 2019

This article proposes a monitoring system that allows to track transitions between different stages in the berry harvesting process (berry picking, waiting for transport, transport and arrival at the packing site) solely using information from temperature and vibration sensors located in the basket. The monitoring system assumes a characterization of the process based on hidden Markov models and uses the Viterbi algorithm to perform inferences and estimate the most likely state trajectory. The obtained state trajectory estimate is then used to compute a potential damage indicator in real time. The proposed methodology does not require information about the weight of the basket to identify each of the different stages, which makes it effective and more efficient than other alternatives available in the industry.
Research on Method of Farmland Obstacle Boundary Extraction in UAV Remote Sensing Images
Authors: Fang Hui , Chen Hai , Jiang Hao , Wang Yu , Liu Yufei , Liu Fei , He Yong
Published: October 2019

Aimed at the problem of obstacle detection in farmland, the research proposed to adopt the method of farmland information acquisition based on unmanned aerial vehicle landmark image, and improved the method of extracting obstacle boundary based on standard correlation coefficient template matching and assessed the influence of different image resolutions on the precision of obstacle extraction. Analyzing the RGB image of farmland acquired by unmanned aerial vehicle remote sensing technology, this research got the following results. Firstly, we applied a method automatically registering coordinates, and the average deviations on the X and Y direction were 4.6 cm and 12.0 cm respectively, while the average deviations manually by ArcGIS were 4.6 cm and 5.7 cm. Secondly, with an improvement on the step of the traditional correlation coefficient template matching, we reduced the time of template matching from 12.2 s to 4.6 s. The average deviation between edge length of obstacles calculated by corner points extracted by the algorithm and that by actual measurement was 4.0 cm. Lastly, by compressing the original image on a different ratio, when the pixel reached 735 × 2174 (the image resolution reached 6 cm), the obstacle boundary was extracted based on correlation coefficient template matching, the average deviations of boundary points I of six obstacles on the X and Y were respectively 0.87 and 0.95 cm, and the whole process of detection took about 3.1 s. To sum up, it can be concluded that the algorithm of automatically registered coordinates and of automatically extracted obstacle boundary, which were designed in this research, can be applied to the establishment of a basic information collection system for navigation in future study. The best image pixel of obstacle boundary detection proposed after integrating the detection precision and detection time can be the theoretical basis for deciding the unmanned aerial vehicle remote sensing image resolution.
Self-Tuning Distributed Fusion Filter for Multi-Sensor Networked Systems with Unknown Packet Receiving Rates, Noise Variances, and Model Parameters
Authors: Wang Minhui , Sun Shuli
Published: October 2019

In this study, we researched the problem of self-tuning (ST) distributed fusion state estimation for multi-sensor networked stochastic linear discrete-time systems with unknown packet receiving rates, noise variances (NVs), and model parameters (MPs). Packet dropouts may occur when sensor data are sent to a local processor. A Bernoulli distributed stochastic variable is adopted to depict phenomena of packet dropouts. By model transformation, the identification problem of packet receiving rates is transformed into that of unknown MPs for a new augmented system. The recursive extended least squares (RELS) algorithm is used to simultaneously identify packet receiving rates and MPs in the original system. Then, a correlation function method is used to identify unknown NVs. Further, a ST distributed fusion state filter is achieved by applying identified packet receiving rates, NVs, and MPs to the corresponding optimal estimation algorithms. It is strictly proven that ST algorithms converge to optimal algorithms under the condition that the identifiers for parameters are consistent. Two examples verify the effectiveness of the proposed algorithms.
Hands-Free User Interface for AR/VR Devices Exploiting Wearer’s Facial Gestures Using Unsupervised Deep Learning
Authors: Cha Jaekwang , Kim Jinhyuk , Kim Shiho
Published: October 2019

Developing a user interface (UI) suitable for headset environments is one of the challenges in the field of augmented reality (AR) technologies. This study proposes a hands-free UI for an AR headset that exploits facial gestures of the wearer to recognize user intentions. The facial gestures of the headset wearer are detected by a custom-designed sensor that detects skin deformation based on infrared diffusion characteristics of human skin. We designed a deep neural network classifier to determine the user’s intended gestures from skin-deformation data, which are exploited as user input commands for the proposed UI system. The proposed classifier is composed of a spatiotemporal autoencoder and deep embedded clustering algorithm, trained in an unsupervised manner. The UI device was embedded in a commercial AR headset, and several experiments were performed on the online sensor data to verify operation of the device. We achieved implementation of a hands-free UI for an AR headset with average accuracy of 95.4% user-command recognition, as determined through tests by participants.
Authentication Protocol for Cloud Databases Using Blockchain Mechanism
Authors: Deep Gaurav , Mohana Rajni , Nayyar Anand , Sanjeevikumar P. , Hossain Eklas
Published: October 2019

Cloud computing has made the software development process fast and flexible but on the other hand it has contributed to increasing security attacks. Employees who manage the data in cloud companies may face insider attack, affecting their reputation. They have the advantage of accessing the user data by interacting with the authentication mechanism. The primary aim of this research paper is to provide a novel secure authentication mechanism by using Blockchain technology for cloud databases. Blockchain makes it difficult to change user login credentials details in the user authentication process by an insider. The insider is not able to access the user authentication data due to the distributed ledger-based authentication scheme. Activity of insider can be traced and cannot be changed. Both insider and outsider user’s are authenticated using individual IDs and signatures. Furthermore, the user access control on the cloud database is also authenticated. The algorithm and theorem of the proposed mechanism have been given to demonstrate the applicability and correctness.The proposed mechanism is tested on the Scyther formal system tool against denial of service, impersonation, offline guessing, and no replay attacks. Scyther results show that the proposed methodology is secure cum robust.