bluuebunny/crossref_metadata_2025 huggingface dataset:
A Fast Sparse Coding Method for Image Classification
Authors: Zang Mujun , Wen Dunwei , Liu Tong , Zou Hailin , Liu Chanjuan
Published: February 2019

Image classification is an important problem in computer vision. The sparse coding spatial pyramid matching (ScSPM) framework is widely used in this field. However, the sparse coding cannot effectively handle very large training sets because of its high computational complexity, and ignoring the mutual dependence among local features results in highly variable sparse codes even for similar features. To overcome the shortcomings of previous sparse coding algorithm, we present an image classification method, which replaces the sparse dictionary with a stable dictionary learned via low computational complexity clustering, more specifically, a k-medoids cluster method optimized by k-means++. The proposed method can reduce the learning complexity and improve the feature’s stability. In the experiments, we compared the effectiveness of our method with the existing ScSPM method and its improved versions. We evaluated our approach on two diverse datasets: Caltech-101 and UIUC-Sports. The results show that our method can increase the accuracy of spatial pyramid matching, which suggests that our method is capable of improving performance of sparse coding features.
Comparing Statistical and Semi-Distributed Rainfall–Runoff Models for a Large Subtropical Watershed: A Case Study of Jiulong River Catchment, China
Authors: Han XianXian , Li GaoYang , Lu WenFang , Jiang YuWu
Published: February 2019

In this contribution, the authors present their preliminary investigations into modeling the rainfall–runoff generation relation in a large subtropical catchment (Jiulong River catchment) on the southeast coast of China. Previous studies have mostly focused on modeling the streamflow and water quality of its small rural subcatchments. However, daily runoff on the scale of the whole catchment has not been modeled before, and hourly runoff data are desirable for some oceanographic applications. Three methods are proposed for modeling streamflow using rainfall outputted by the Weather Research Forecast (WRF) model, calculated potential evaporation (PET), and land cover type: (i) a ridge regression model; (ii) NPRED-KNN: a nonparametric k-nearest neighbor model (KNN) employing a parameter selection method (NPRED) based on partial information coefficient; (iii) the Hydrological Simulation Program-Fortran (HSPF) model with an hourly time step. Results show that the NPRED-KNN approach is the most unsuitable method of those tested. The HSPF model was manually calibrated, and ridge regression performs no worse than HSPF based on daily verification, whilst HSPF can produce realist daily flow time series, of which ridge regression is incapable. The HSPF model seems less prone to systematic underprediction when replicating monthly-annual water balance, and it successfully replicates the baseflow index (the flow intensity) of the Jiulong River catchment system.
Interval Methods with Fifth Order of Convergence for Solving Nonlinear Scalar Equations
Authors: Ivanov Ivan G. , Mateva Tonya
Published: February 2019

In this paper, based on Kou’s classical iterative methods with fifth-order of convergence, we propose new interval iterative methods for computing a real root of the nonlinear scalar equations. Some numerical experiments have executed with the program INTLAB in order to confirm the theoretical results. The computational results have described and compared with Newton’s interval method, Ostrowski’s interval method and Ostrowski’s modified interval method. We conclude that the proposed interval schemes are effective and they are comparable to the classical interval methods.
Advanced Numerical Methods in Applied Sciences
Authors: Brugnano Luigi , Iavernaro Felice
Published: February 2019

The use of scientific computing tools is, nowadays, customary for solving problems in Applied Sciences at several levels of complexity. The great need for reliable software in the scientific community conveys a continuous stimulus to develop new and more performing numerical methods which are able to grasp the particular features of the problem at hand. This has been the case for many different settings of numerical analysis, and this Special Issue aims at covering some important developments in various areas of application.
Recent Advances in Non-Flammable Electrolytes for Safer Lithium-Ion Batteries
Authors: Chawla Neha , Bharti Neelam , Singh Shailendra
Published: February 2019

Lithium-ion batteries are the most commonly used source of power for modern electronic devices. However, their safety became a topic of concern after reports of the devices catching fire due to battery failure. Making safer batteries is of utmost importance, and several researchers are trying to modify various aspects in the battery to make it safer without affecting the performance of the battery. Electrolytes are one of the most important parts of the battery since they are responsible for the conduction of ions between the electrodes. In this paper, we discuss the different non-flammable electrolytes that were developed recently for safer lithium-ion battery applications.
Parkinsonisms and Glucocerebrosidase Deficiency: A Comprehensive Review for Molecular and Cellular Mechanism of Glucocerebrosidase Deficiency
Authors: Gatto Emilia , Da Prat Gustavo , Etcheverry Jose , Drelichman Guillermo , Cesarini Martin
Published: February 2019

In the last years, lysosomal storage diseases appear as a bridge of knowledge between rare genetic inborn metabolic disorders and neurodegenerative diseases such as Parkinson’s disease (PD) or frontotemporal dementia. Epidemiological studies helped promote research in the field that continues to improve our understanding of the link between mutations in the glucocerebrosidase (GBA) gene and PD. We conducted a review of this link, highlighting the association in GBA mutation carriers and in Gaucher disease type 1 patients (GD type 1). A comprehensive review of the literature from January 2008 to December 2018 was undertaken. Relevance findings include: (1) There is a bidirectional interaction between GBA and α- synuclein in protein homeostasis regulatory pathways involving the clearance of aggregated proteins. (2) The link between GBA deficiency and PD appears not to be restricted to α–synuclein aggregates but also involves Parkin and PINK1 mutations. (3) Other factors help explain this association, including early and later endosomes and the lysosomal-associated membrane protein 2A (LAMP-2A) involved in the chaperone-mediated autophagy (CMA). (4) The best knowledge allows researchers to explore new therapeutic pathways alongside substrate reduction or enzyme replacement therapies.
MEK Inhibition Induces Canonical WNT Signaling through YAP in KRAS Mutated HCT-15 Cells, and a Cancer Preventive FOXO3/FOXM1 Ratio in Combination with TNKS Inhibition
Authors: Solberg Nina Therese , Melheim Maria , Strand Martin Frank , Olsen Petter Angell , Krauss Stefan
Published: February 2019

The majority of colorectal cancers are induced by subsequent mutations in APC and KRAS genes leading to aberrant activation of both canonical WNT and RAS signaling. However, due to induction of feedback rescue mechanisms some cancers do not respond well to targeted inhibitor treatments. In this study we show that the APC and KRAS mutant human colorectal cancer cell line HCT-15 induces canonical WNT signaling through YAP in a MEK dependent mechanism. This inductive loop is disrupted with combined tankyrase (TNKS) and MEK inhibition. RNA sequencing analysis suggests that combined TNKS/MEK inhibition induces metabolic stress responses in HCT-15 cells promoting a positive FOXO3/FOXM1 ratio to reduce antioxidative and cryoprotective systems.
Direct Synthesis of Hydrogen Peroxide under Semi-Batch Conditions over Un-Promoted Palladium Catalysts Supported by Ion-Exchange Sulfonated Resins: Effects of the Support Morphology
Authors: Frison Francesco , Dalla Valle Chiara , Evangelisti Claudio , Centomo Paolo , Zecca Marco
Published: February 2019

Palladium catalysts supported by a mesoporous form of sulfonated poly-divinylbenzene, Pd/µS-pDVB10 (1%, w/w) and Pd/µS-pDVB35 (3.6% w/w), were applied to the direct synthesis of hydrogen peroxide from dihydrogen and dioxygen. The reaction was carried for 4 h out in a semibatch reactor with continuous feed of the gas mixture (H2/O2 = 1/24, v/v; total flow rate 25 mL·min−1), at 25 °C and 101 kPa. The catalytic performances were compared with those of a commercial egg-shell Pd/C catalyst (1%, w/w) and of a palladium catalyst supported by a macroreticular sulfonated ion-exchange resin, Pd/mS-pSDVB10 (1%, w/w). Pd/µS-pDVB10 and Pd/C showed the highest specific activity (H2 consumption rate of about 75–80 h−1), but the resin supported catalyst was much more selective (ca 50% with no promoters). The nanoparticles (NP) size was somewhat larger in Pd/µS-pDVB10, showing that either the reaction was structure insensitive or diffusion limited to some extent over Pd/C, in which the support is microporous. The open pore structure of Pd/µS-pDVB10, possibly ensuring the fast removal of H2O2 from the catalyst, could also be the cause of the relatively high selectivity of this catalyst. In summary, Pd/µS-pDVB10 was the most productive catalyst, forming ca 375 molH2O2·kgPd−1·h−1, also because it retained a constant selectivity, while the other ones underwent a more or less pronounced loss of selectivity after 80–90 min. Ageing experiments showed that for a palladium catalyst supported on sulfonated mesoporous poly-divinylbenzene storage under oxidative conditions implied some deactivation, but a lower drop in the selectivity; regeneration upon a reductive treatment or storage under strictly anaerobic conditions (dry-box) lead to an increase of the activity but to both a lower initial selectivity and a higher drop of selectivity with time.
Immobilization of Stabilized Gold Nanoparticles on Various Ceria-Based Oxides: Influence of the Protecting Agent on the Glucose Oxidation Reaction
Authors: Chenouf Meriem , Megías-Sayago Cristina , Ammari Fatima , Ivanova Svetlana , Centeno Miguel Angel , Odriozola José Antonio
Published: February 2019

The influence of the protecting agent’s nature on gold particle size and dispersion was studied in this work over a series of gold-based catalysts. CO and glucose oxidation were chosen as catalytic reactions to determine the catalyst’s structure–activity relationship. The nature of the support appeared to be the predominant factor for the increase in activity, as the oxygen mobility was decisive for the CO oxidation in the same way that the Lewis acidity was decisive for the glucose oxidation. For the same catalyst composition, the use of montmorillonite as the stabilizing agent resulted in better catalytic performance.
Stability and Activity of Zn/MCM-41 Materials in Toluene Alkylation: Microwave Irradiation vs Continuous Flow
Authors: Carraro Paola M. , Goldani Bruna S. , Alves Diego , Sathicq A. Gabriel , Eimer Griselda A. , Romanelli Gustavo P. , Luque Rafael
Published: February 2019

Zn/MCM-41 mesoporous materials have been prepared via classic wet impregnation, employing zinc nitrate as precursor and tested for activity and stability in the Friedel-Crafts alkylation of toluene with benzyl chloride under microwave irradiation and continuous flow. The modified materials were characterized by means of a number of analytical techniques, and surface and textural properties were thoroughly checked. Materials containing the highest Zn loading (15 wt %) provided full conversion after 5 min reaction under microwave irradiation (300 W, 120 °C). Materials were proved to be stable and reusable for several cycles with an optimum performance under continuous flow conditions.
Constraints to Vegetation Growth Reduced by Region-Specific Changes in Seasonal Climate
Authors: Hashimoto Hirofumi , Nemani Ramakrishna , Bala Govindasamy , Cao Long , Michaelis Andrew , Ganguly Sangram , Wang Weile , Milesi Cristina , Eastman Ryan , Lee Tsengdar , Myneni Ranga
Published: February 2019

We qualitatively and quantitatively assessed the factors related to vegetation growth using Earth system models and corroborated the results with historical climate observations. The Earth system models showed a systematic greening by the late 21st century, including increases of up to 100% in Gross Primary Production (GPP) and 60% in Leaf Area Index (LAI). A subset of models revealed that the radiative effects of CO2 largely control changes in climate, but that the CO2 fertilization effect dominates the greening. The ensemble of Earth system model experiments revealed that the feedback of surface temperature contributed to 17% of GPP increase in temperature-limited regions, and radiation increase accounted for a 7% increase of GPP in radiation-limited areas. These effects are corroborated by historical observations. For example, observations confirm that cloud cover has decreased over most land areas in the last three decades, consistent with a CO2-induced reduction in transpiration. Our results suggest that vegetation may thrive in the starkly different climate expected over the coming decades, but only if plants harvest the sort of hypothesized physiological benefits of higher CO2 depicted by current Earth system models.
Improved Electronic Transport in Ion Complexes of Crown Ether Based Columnar Liquid Crystals
Authors: Staffeld Peter , Kaller Martin , Ehni Philipp , Ebert Max , Laschat Sabine , Giesselmann Frank
Published: February 2019

The Li+- and K+-complexes of new discotic mesogens, where two n-alkoxy-substituted triphenylene cores are connected by a central crown ether (12-crown-4 and 18-crown-6), provide interesting structural and electronic properties. The inter- and intra-columnar structure was investigated by small and wide angle X-ray scattering. The electronic and ionic transports were studied by temperature dependent photoconductivity and impedance spectroscopy, respectively. Besides a strong increase of the stability and the width of the columnar phases the presence of soft anions (iodide, thiocyanate, tetrafluoroborate) leads to an improved intra-columnar order. The hereby shortened stacking-distance of the triphenylene cores leads to a significant increase of the photoconductivity in the columnar mesophase. Furthermore, the ionic conductivity of the new materials was investigated on macroscopically aligned thin films. The existence of channels for fast cation transport formed by the stacked crown ether moieties in the centre of each column can be excluded. The cations are coordinated strongly and therefore contributing only little to the conductivity. The ionic conductivity is dominated by the anisotropic migration of the non-coordinated anions through the liquid, like side chains favouring the propagation parallel to the columns. Iodide migrates about 20 times faster than thiocyanate and 100 times faster than tetrafluoroborate.
Investigation of the Peninsula Effect Using the Latitudinal Abundance Pattern for Tree Species in Florida
Authors: Kwon Youngsang , Feng Lian
Published: February 2019

The peninsula effect is a biological diversity pattern found in peninsulas in which the number of species decreases toward the tip of the peninsula. The geometry hypothesis, as one proposed cause of the peninsula effect, attempts to predict this pattern by examining the peculiarities of peninsular geometry. As peninsulas are characterized by their isolated positions, it has been suggested that a decreased immigration-to-extinction rate is the cause of the decrease in species diversity from the base to the tip of a peninsula. We aimed to test the geometry hypothesis on tree species in the Florida peninsula by modeling the latitudinal abundance pattern using sample-based tree inventory data. We postulated that the current abundance distribution of a species is a ramification of past immigration–extinction dynamics in a peninsula, as well as an important indicator of such dynamics in the future. The latitudinal abundance patterns of 113 tree species in Florida in the southeastern United States were simulated with the Huisman–Olff–Fresco (HOF) model using the USDA Forest Service’s Forest Inventory and Analysis (FIA) database. Evidence species for the geometry hypothesis were then selected if the simulated latitudinal abundance pattern was asymmetric with its abundance maxima occurring within the Florida peninsula (i.e., approximately 31.5° latitude or lower). Our HOF model results found that most species (87% of 113 species) did not experience any steep abundance decline along the Florida peninsula when compared with their general trend across the range, suggesting that the observed diversity pattern of tree species in Florida could merely be a continuation of latitudinal diversity gradients in the southeastern United States, independent of peninsular geometry.
Autophagy Intertwines with Different Diseases—Recent Strategies for Therapeutic Approaches
Authors: Ramesh Janani , Ronsard Larance , Gao Anthony , Venugopal Bhuvarahamurthy
Published: February 2019

Autophagy is a regular and substantial “clear-out process” that occurs within the cell and that gets rid of debris that accumulates in membrane-enclosed vacuoles by using enzyme-rich lysosomes, which are filled with acids that degrade the contents of the vacuoles. This machinery is well-connected with many prevalent diseases, including cancer, HIV, and Parkinson’s disease. Considering that autophagy is well-known for its significant connections with a number of well-known fatal diseases, a thorough knowledge of the current findings in the field is essential in developing therapies to control the progression rate of diseases. Thus, this review summarizes the critical events comprising autophagy in the cellular system and the significance of its key molecules in manifesting this pathway in various diseases for down- or upregulation. We collectively reviewed the role of autophagy in various diseases, mainly neurodegenerative diseases, cancer, inflammatory diseases, and renal disorders. Here, some collective reports on autophagy showed that this process might serve as a dual performer: either protector or contributor to certain diseases. The aim of this review is to help researchers to understand the role of autophagy-regulating genes encoding functional open reading frames (ORFs) and its connection with diseases, which will eventually drive better understanding of both the progression and suppression of different diseases at various stages. This review also focuses on certain novel therapeutic strategies which have been published in the recent years based on targeting autophagy key proteins and its interconnecting signaling cascades.
The Presence of Gut Microbial Genes Encoding Bacterial Genotoxins or Pro-Inflammatory Factors in Stool Samples from Individuals with Colorectal Neoplasia
Authors: Gómez-Moreno Ramón , González-Pons María , Soto-Salgado Marievelisse , Cruz-Correa Marcia , Baerga-Ortiz Abel
Published: February 2019

Gut bacterial toxins are thought to contribute to the development of colorectal cancer (CRC). This study examines the presence of specific gut bacterial toxin genes in stool samples from individuals with colorectal neoplasia (adenomas and/or CRC). The presence of bacterial genes encoding genotoxic or pro-inflammatory factors (pks, tcpC, gelE, cnf-1, AMmurB, and usp) was established by PCR of stool samples from individuals from mainland US (n = 30; controls = 10, adenoma = 10, CRC = 10) and from Puerto Rico (PR) (n = 33; controls = 13; adenomas = 8; CRC = 12). Logistic regression models and multinomial logistic regression models were used to estimate the magnitude of association. Distinct bacterial gene profiles were observed in each sample cohort. In individuals with CRC, AMmurB was detected more frequently in samples from the US and gelE in samples from PR. In samples from PR, individuals with ≥2 gut bacterial toxin genes in stool had higher odds of having colorectal neoplasia (OR = 11.0, 95%: CI 1.0–637.1): however, no significant association between bacterial genes and colorectal neoplasia was observed in the US cohort. Further analyses are warranted in a larger cohort to validate these preliminary findings, but these encouraging results highlight the importance of developing bacterial markers as tools for CRC diagnosis or risk stratification.
Hybrid Feature Extraction for Detection of Degree of Motor Fluctuation Severity in Parkinson’s Disease Patients
Authors: Hssayeni Murtadha D. , Jimenez-Shahed Joohi , Ghoraani Behnaz
Published: February 2019

The success of medication adjustment in Parkinson’s disease (PD) patients with motor fluctuation relies on the knowledge about their fluctuation severity. However, because of the temporal and spatial variability in motor fluctuations, a single clinical examination often fails to capture the spectrum of motor impairment experienced in routine daily life. In this study, we developed an algorithm to estimate the degree of motor fluctuation severity from two wearable sensors’ data during subjects’ free body movements. Specifically, we developed a new hybrid feature extraction method to represent the longitudinal changes of motor function from the sensor data. Next, we developed a classification model based on random forest to learn the changes in the patterns of the sensor data as the severity of the motor function changes. We evaluated our algorithm using data from 24 subjects with idiopathic PD as they performed a variety of daily routine activities. A leave-one-subject-out assessment of the algorithm resulted in 83.33% accuracy, indicating that our approach holds a great promise to passively detect degree of motor fluctuation severity from continuous monitoring of an individual’s free body movements. Such a sensor-based assessment system and algorithm combination could provide the objective and comprehensive information about the fluctuation severity that can be used by the treating physician to effectively adjust therapy for PD patients with troublesome motor fluctuation.
Macroeconomic Determinants of Stock Market Fluctuations: The Case of BIST-100
Authors: Demir Caner
Published: February 2019

The purpose of this study is to analyze the impacts of some prominent macroeconomic factors on the Turkish Stock Market index, BIST-100 (Borsa Istanbul-100). For centuries, and mostly since the 20th century, stock markets are at the heart of economies. In our era, the largest economic crises arise from the stock market instabilities and thus, the stock markets are the focus of interest of the economy. Economists, investors, and policymakers try to predict the tendency of share prices, which substantially depend on foreign and domestic macroeconomic factors. Within this purpose, this study tries to investigate the impact of some selected macroeconomic factors on BIST-100 index over the 2003Q1–2017Q4 period. The findings obtained from the quarterly data via the ARDL Bounds Test suggest that economic growth, the relative value of the domestic currency, portfolio investments and foreign direct investments raise the stock market index while interest rate and crude oil prices negatively affect it. The results briefly reveal that the Istanbul Stock Exchange Market needs stronger domestic currency, higher international capital inflows, and lower energy and investment costs.
Mitigating the Load Frequency Fluctuations of Interconnected Power Systems Using Model Predictive Controller
Authors: Gulzar Muhammad , Rizvi Syed , Javed Muhammad , Sibtain Daud , Salah ud Din Rubab
Published: February 2019

The penetration of renewable energy sources into the conventional power systems are evolving day by day. Therefore, in this paper, a photovoltaic (PV) connected thermal system is discussed and analyzed by keeping PV to operate at maximum power point (MPP). The main problem in the interconnection of these systems is load frequency fluctuations due to different load changing conditions. The model predictive controller (MPC) has the ability to predict the target value at real-time with fast convergence. Therefore, MPC is proposed to negate this problem by giving minimum oscillation. The comparison analysis is carried out with other conventional controllers, including genetic algorithm-based PI, firefly algorithm-based PI and PI controller. Simulation results clearly exhibit the outclass performance of MPC over all other controllers.
Dual Authentication-Based Encryption with a Delegation System to Protect Medical Data in Cloud Computing
Authors: Badr Aymen Mudheher , Zhang Yi , Ahmad Umar Hafiz Gulfam
Published: February 2019

The increasing use of cloud computing, especially in commercial, government and healthcare institutions, started with the use of computerized clouds. Clouds store important data, which reduces the cost of management and ensures easy access. To protect this data, cryptographic methods are used to ensure confidentiality of the data, as well as to secure access to user data and increase trust in cloud technology. In our paper, we suggest a new scheme to support an attribute-based encryption system (ABE) that involves multiple parties such as data owners, data users, cloud servers and authority. A verified and authenticated decryption process for the cloud environment is the imperative feature of our proposed architecture. The data owner encrypts their data and sends it to the cloud. The cloud server performs partial decryption and the final decrypted data are shared for users as per their privileges. Thus, the data owner reduces complexity of productivity by delegating the decryption process to the cloud server. Analysis of the experimental results confirms that data access in the electronic cloud atmosphere is safer due to a controlled multiple-users-rights scheme. Our performance evaluation results show that the proposed model condensed the communication overhead and made Digital Imaging and Communications in Medicine (DICOM) more secure.
Impact Analysis of Survivability-Oriented Demand Response on Islanded Operation of Networked Microgrids with High Penetration of Renewables
Authors: Park Sung-Ho , Hussain Akhtar , Kim Hak-Man
Published: February 2019

Microgrids have the potential to withstand the power outages due to their ability of islanding and potential to sustain the penetration of renewables. Increased penetration of renewables can be beneficial but it may result in curtailment of renewables during peak generation intervals due to the limited availability of storage capacity while shedding loads during peak load intervals. This problem can be solved by adjusting the load profiles, i.e., demand response (DR) programs. In contrast to the existing studies, where DR is triggered by market price signals, a local resource-triggered survivability-oriented demand response program is proposed in this paper. The proposed DR program is triggered by renewable and load level of the microgrid with an objective to minimize the load shedding and curtailment of renewables. The uncertainties in load and renewables are realized via a robust optimization method and the worst-case scenario is considered. The performance of the proposed method is compared with two conventional operation cases, i.e., independent operation case and interconnected operation case without DR. In addition, the impact of renewable penetration level, amount of shiftable load, and load absorption capacity on the performance of the proposed method are also analyzed. Simulation results have proved the proposed method is capable of reducing load shedding, renewable curtailment, and operation cost of the network during emergencies.
Consensus-Based Method for Anomaly Detection in VAV Units
Authors: Mattera Claudio Giovanni , Shaker Hamid Reza , Jradi Muhyiddine
Published: February 2019

Buildings account for large part of global energy consumption. Besides energy consumed due to normal operation, a large amount of energy can be wasted due to faults in buildings subsystems. Fault detection and diagnostics techniques aim to identify faults and prevent energy waste, but are often difficult to apply in practice. Data-driven methods, in particular, require an adequate amount of fault-free training data, which is rarely available. In this paper, we propose a method for anomaly detection that exploits consensus among multiple identical components. Even if some of the components are faulty, their aggregate behaviour is overall correct, and it can be used to train a data-driven model. We test our method on variable-air-volume units in an existing building, executing two experiments grouping the components according to ventilation unit, and according to room type. The two experiments identified the same set of anomalous components, i.e., their behaviour was different from the rest of the group in both cases, and this suggests that the anomaly was not due to wrong group assignment. The proposed method shows the potential of exploiting consensus among multiple identical systems to detect anomalous ones.
Net Electricity and Heat Generated by Reusing Mediterranean Agro-Industrial By-Products
Authors: Valenti Francesca , Porto Simona M. C.
Published: February 2019

The necessity to investigate suitable alternatives to conventional fossil fuels has increased interest in several renewable energy resources, especially in biomasses that are widely available and make it possible to reach environmental and socio-economic improvements. Among solutions for bioenergy production, anaerobic digestion technology allows biogas production by reusing agricultural residues and agro-industrial by-products. By considering the basic concepts of the Biogasdoneright® method, the objective of this study was to estimate the theoretical potential net electricity and heat production from anaerobic digestion of citrus pulp and olive pomace highly available worldwide. A model was developed and applied in a study area of the Mediterranean basin, where the biogas sector is still very limited despite the importance of both agricultural and agro-industrial activities, especially with regard to citrus and olive cultivation processing. Firstly, the application of a geographical information system (GIS) software tool allowed the estimation of the biogas potentially produced from citrus pulp and olive pomace re-use. Then, the development of a technical assessment demonstrated that 15.9 GWh electricity and 88,000 GJ heat per year could be generated from these by-products, satisfying approximate 17% of the electricity demand of the agricultural sector of the study area (90.2 GWh y−1). The achieved results could be relevant with regard to the intervention priorities established by the European Union related to the planning activities supported by the European Structural and Investment Funds within the Smart Specialisation Strategy.
Development of Grid-Connected Inverter Experiment Modules for Microgrid Learning
Authors: Rizqiawan Arwindra , Hadi Pradita , Fujita Goro
Published: February 2019

New paradigms in the modern power system should be introduced to student of electrical engineering, or engineer in training, as early as possible. Besides class-room study, experimental exercise may be introduced to help the student understand the concept of microgrid. One main challenge is the power electronics converter, which connects the distributed energy source to the existing power grid. This study modeled and developed a grid-connected inverter that is useful for providing a close to real application for a student or engineer in training. This development is important for microgrid learning to give practical perspective to the student. A grid-connected inverter for distributed generation was developed at laboratory scale. The grid-connected inverter was developed modularly to make it easier for the student to understand the basic concept of grid-connected inverter building blocks, as well as its function as a whole. The developed grid-connected inverter was intended to be able to operate on two different mode: grid-forming mode and grid-injecting mode. Experiments were conducted to verify the results.
Cross Regulation Reduced Optimal Multivariable Controller Design for Single Inductor DC-DC Converters
Authors: Augusti Lindiya S. , Subashini N. , Vijayarekha K.
Published: February 2019

Single Inductor (SI) converters with the advantage of using one inductor for any number of inputs/outputs find wide applications in portable electronic gadgets and electrical vehicles. SI converters can be used in Single Input Multiple Output (SIMO) and Multiple Input Multiple Output (MIMO) configurations but they need controllers to achieve good transient and steady state responses, to improve the stability against load and line disturbances and to reduce cross regulation. Cross regulation is the change in an output voltage due to change in the load current at another output and it is an added constraint in SI converters. In this paper, Single Input Dual Output (SIDO) and Dual Input Dual Output (DIDO) converters with applications capable of handling high load current working in Continuous Conduction Mode (CCM) of operation are taken under study. Conventional multivariable PID and optimal Linear Quadratic Regulator (LQR) controllers are developed and their performances are compared for the above configurations to meet the desired objectives. Generalized mathematical models for SIMO and MIMO are developed and a Genetic Algorithm (GA) is used to find the parameters of a multivariable PID controller and the weighting matrices of optimal LQR where the objective function includes cross regulation as a constraint. The simulated responses reveal that LQR controller performs well for both the systems over multivariable PID controller and they are validated by hardware prototype model with the help of DT9834® Data Acquisition Module (DAQ). The methodologies used here generate a fresh dimension for the case of such converters in practical applications.
The Stability of Mean Wood Specific Gravity across Stand Age in US Forests Despite Species Turnover
Authors: Healey Sean P. , Menlove James
Published: February 2019

Research Highlights: Estimates using measurements from a sample of approximately 132,000 field plots imply that while the species composition of US forests varies substantially across different age groups, the specific gravity of wood in those forests does not. This suggests that models using increasingly accurate spaceborne measurements of tree size to model forest biomass do not need to consider stand age as a covariate, greatly reducing model complexity and calibration data requirements. Background and Objectives: Upcoming lidar and radar platforms will give us unprecedented information about how big the trees around the world are. To estimate biomass from these measurements, one must know if tall trees in young stands have the same biomass density as trees of equal size in older stands. Conventional succession theory suggests that fast-growing pioneers often have lower wood (and biomass) density than the species that eventually dominate older stands. Materials and Methods: We used a nationally consistent database of field measurements to analyze patterns of both wood specific gravity (WSG) across age groups in the United States and changes of species composition that would explain any shifts in WSG. Results: Shifts in species composition were observed across 12 different ecological divisions within the US, reflecting both successional processes and management history impacts. However, steady increases in WSG with age were not observed, and WSG differences were much larger across ecosystems than across within-ecosystem age groups. Conclusions: With no strong evidence that age is important in specifying how much biomass to ascribe to trees of a particular size, field data collection can focus on acquiring reference data in poorly sampled ecosystems instead of expanding existing samples to include a range of ages for each level of canopy height.
Where Did You Come From? Where Did You Go? Investigating the Origin of Invasive Leptocybe Species Using Distribution Modelling
Authors: Otieno Beryn A. , Nahrung Helen F. , Steinbauer Martin J.
Published: February 2019

Research Highlights: We present the first attempts to model the distributions of the two cryptic and globally invasive species of Leptocybe invasa sensu lato (Fisher & LaSalle) (Hymenoptera: Eulophidae) in its purported country of origin, namely Australia. Background and Objectives: Leptocybe invasa is an invasive eucalypt-galling wasp that spread quickly all over the world in the early to mid-2000’s, achieving significant pest status through its severe impacts on the growth and productivity of extra-limital eucalypt plantations. Until its discovery in Europe and the Middle East, the genus was undescribed, and its native range remains unclear. Molecular studies indicate the globally invasive population comprises two cryptic species with variable modes of reproduction. Collection records from Australia, the purported origin, represent only one of the invasive lineages, restricted to subtropical and tropical Queensland and northern New South Wales. To date, the original invasive lineage has not been found in Australia, despite searches over the seventeen years that it has been spreading overseas. Materials and Methods: To understand the distributions of the invasive populations, and to infer Leptocybe spp. native ranges within Australia, we used correlative niche modelling in Maximum Entropy (MaxEnt) and multivariate analysis, and created a CLIMEX model based on development rates of an invasive population. Results: We used the environmental conditions in the extra-limital range to infer possible origins, with our findings supporting the possibility that the invasive populations may have originated from different populations in Australia. Conclusions: We highlight the need for better understanding of the distribution, genetic diversity, and reproductive mode of the species within Australia. The variety of climatic niches occupied by invasive lineages of the wasp potentially present new threats to eucalypts in previously uninfested habitats.
Continuous Fiber Angle Topology Optimization for Polymer Composite Deposition Additive Manufacturing Applications
Authors: Jiang Delin , Hoglund Robert , Smith Douglas E.
Published: February 2019

Mechanical properties of parts produced with polymer deposition additive manufacturing (AM) depend on the print bead direction, particularly when short carbon-fiber reinforcement is added to the polymer feedstock. This offers a unique opportunity in the design of these structures since the AM print path can potentially be defined in a direction that takes advantage of the enhanced stiffness gained in the bead and, therefore, fiber direction. This paper presents a topology optimization approach for continuous fiber angle optimization (CFAO), which computes the best layout and orientation of fiber reinforcement for AM structures. Statically loaded structures are designed for minimum compliance where the adjoint variable method is used to compute design derivatives, and a sensitivity filter is employed to reduce the checkerboard effect. The nature of the layer-by-layer approach in AM is given special consideration in the algorithm presented. Examples are provided to demonstrate the applicability of the method in both two and three dimensions. The solution to our two dimensional problem is then printed with a fused filament fabrication (FFF) desktop printer using the material distribution results and a simple infill method which approximates the optimal fiber angle results using a contour-parallel deposition strategy. Mechanical stiffness testing of the printed parts shows improved results as compared to structures designed without accounting for the direction of the composite structure. Results show that the mechanical properties of the final FFF carbon fiber/polymer composite printed parts are greatly influenced by the print direction, and optimized material orientation tends to align with the imposed force direction to minimize the compliance.
Quality and Nutritional/Textural Properties of Durum Wheat Pasta Enriched with Cricket Powder
Authors: Duda Adamina , Adamczak Julia , Chełmińska Paulina , Juszkiewicz Justyna , Kowalczewski Przemysław
Published: February 2019

Cricket powder (CP) contains significant amounts of protein, fat (including unsaturated fatty acids), and fiber, as well as vitamins and minerals. The high nutritional value and low price make it an interesting addition to food production. This paper is a report on the results of the addition of cricket powder to pasta. Three levels of durum semolina replacement were chosen: 5%, 10%, and 15%. The obtained products were analyzed for their nutritional composition, cooking and textural properties, and color, as well as consumer acceptance. The results indicate that the addition of CP influenced the cooking weight and cooking loss (reducing losses and water absorption), as well as the color of the pasta, reducing its lightness and shifting color balances to blue and red. The firmness of pasta was also influenced. The firmness was strengthened by addition of CP. Principal components analysis indicated that the flavor change had the most pronounced effect on consumer acceptance. Nevertheless, sensory evaluation proved that protein-enriched pasta produced with CP has consumer acceptance comparable with that of conventional products.
Automated Nuclear Cartography Reveals Conserved Sperm Chromosome Territory Localization across 2 Million Years of Mouse Evolution
Authors: Skinner Benjamin Matthew , Bacon Joanne , Rathje Claudia Cattoni , Larson Erica Lee , Kopania Emily Emiko Konishi , Good Jeffrey Martin , Affara Nabeel Ahmed , Ellis Peter James Ivor
Published: February 2019

Measurements of nuclear organization in asymmetric nuclei in 2D images have traditionally been manual. This is exemplified by attempts to measure chromosome position in sperm samples, typically by dividing the nucleus into zones, and manually scoring which zone a fluorescence in-situ hybridisation (FISH) signal lies in. This is time consuming, limiting the number of nuclei that can be analyzed, and prone to subjectivity. We have developed a new approach for automated mapping of FISH signals in asymmetric nuclei, integrated into an existing image analysis tool for nuclear morphology. Automatic landmark detection defines equivalent structural regions in each nucleus, then dynamic warping of the FISH images to a common shape allows us to generate a composite of the signal within the entire cell population. Using this approach, we mapped the positions of the sex chromosomes and two autosomes in three mouse lineages (Mus musculus domesticus, Mus musculus musculus and Mus spretus). We found that in all three, chromosomes 11 and 19 tend to interact with each other, but are shielded from interactions with the sex chromosomes. This organization is conserved across 2 million years of mouse evolution.
Using Decision Tree Aggregation with Random Forest Model to Identify Gut Microbes Associated with Colorectal Cancer
Authors: Ai Dongmei , Pan Hongfei , Han Rongbao , Li Xiaoxin , Liu Gang , Xia Li C.
Published: February 2019

The imbalance of human gut microbiota has been associated with colorectal cancer. In recent years, metagenomics research has provided a large amount of scientific data enabling us to study the dedicated roles of gut microbes in the onset and progression of cancer. We removed unrelated and redundant features during feature selection by mutual information. We then trained a random forest classifier on a large metagenomics dataset of colorectal cancer patients and healthy people assembled from published reports and extracted and analysed the information from the learned decision trees. We identified key microbial species associated with colorectal cancers. These microbes included Porphyromonas asaccharolytica, Peptostreptococcus stomatis, Fusobacterium, Parvimonas sp., Streptococcus vestibularis and Flavonifractor plautii. We obtained the optimal splitting abundance thresholds for these species to distinguish between healthy and colorectal cancer samples. This extracted consensus decision tree may be applied to the diagnosis of colorectal cancers.
Monsoon-Induced Surge during High Tides at the Southeast Coast of Vietnam: A Numerical Modeling Study
Authors: Thuy Nguyen Ba , Tien Tran Quang , Wettre Cecilie , Hole Lars Robert
Published: February 2019

In this study, monsoon-induced surge during high tides at the Southeast coast of Vietnam was analyzed based on the observed tide data at the Vung Tau station in the period between 1997—2016. Specifically, the surge was determined by removing the astronomical tide from the observed total water level. The two-dimensional Regional Ocean Model System (ROMS 2D) was applied to simulate the surge induced by monsoons during spring tide. The surge observations showed that the change of peak surge did not follow a clear trend, of either an increase or decrease, over time. A peak surge of over 40 cm appeared mainly in October and November, although the peak of the astronomical tide was higher in December. ROMS 2D was validated with the observational data, and the model could sufficiently reproduce the wind-induced surge during high tides. This study therefor ere commends for ROMS 2D to be used in operational forecasts in this area.
Molecular and Isotopic Composition of Hydrate-Bound, Dissolved and Free Gases in the Amazon Deep-Sea Fan and Slope Sediments, Brazil
Authors: Rodrigues Luiz F. , Ketzer João M. , Oliveira Rafael R. , dos Santos Victor H.J.M. , Augustin Adolpho H. , Cupertino Jose A. , Viana Adriano R. , Leonel Bruno , Dorle Wilhelm
Published: February 2019

In this work, we investigated the molecular stable isotope compositions of hydrate-bound and dissolved gases in sediments of the Amazon deep-sea fan and adjacent continental slope, Foz do Amazonas Basin, Brazil. Some cores were obtained in places with active gas venting on the seafloor and, in one of the locations, the venting gas is probably associated with the dissociation of hydrates near the edge of their stability zone. Results of the methane stable isotopes (δ13C and δD) of hydrate-bound and dissolved gases in sediments for the Amazon fan indicated the dominant microbial origin of methane via carbon dioxide reduction, in which 13C and deuterium isotopes were highly depleted (δ13C and δD of −102.2% to −74.2% V-PDB and −190 to −150% V-SMOW, respectively). The combination of C1/(C2+C3) versus δ13C plot also suggested a biogenic origin for methane in all analysed samples (commonly >1000). However, a mixture of thermogenic and microbial gases was suggested for the hydrate-bound and dissolved gases in the continental slope adjacent to the Amazon fan, in which the combination of chemical and isotopic gas compositions in the C1/(C2+C3) versus δ13C plot were <100 in one of the recovered cores. Moreover, the δ13C-ethane of −30.0% indicates a thermogenic origin.