Geospatial assessment on land-use changes of Home Gardens in Upper Mahaweli Catchment in Sri Lanka

Land use changes are altering the hydrologic regimes in a catchment and have potentially large impacts on its water resources. Tree rich Home Gardens (HGs)in the Upper Mahaweli Catchment (UMC) play a vital role in catchment protection while providing other ecological services especially in areas where lack of forest cover. The main objective of this research study was to assess land-use changes of HGs in UMC and to analyze determinants for changes. An integrated approach was adopted for the methodology by integrating geo-spatial technologies with socio-economic modeling. Multi-temporal satellite imagery taken in 1990, 2005 and 2017 used for spatial assessment. Socioeconomic assessment was carried out to assess determinants for changes by developing a Binary logistic regression model using spatial, biophysical, and socio-economic determinants as predictor variables. According to spatial assessment a significant change has been revealed in Nuwara Eliya District of the UMC from 1990 to 2017. The most prominent changes have been occurred during 1990-2005 compared with to 2005 - 2017. During these periods HG land use has been increased by 14.85 % and 5.25%. In contrast, the distinct land use change was the increment of annual crop-based land use by 44.95% during 1990-2005 period. Spatial determinants were positively influenced for the conversion of HGs into other land uses. All other socio-economic determinants except age of the household head were significant for land use changes. Since conversion of HGs into annual cropbased land use would induce reduce tree cover of the UMC which lead to hinder ecological services of catchment protection function derived from HGs, policy strategies should focus on providing sufficient incentives to enhance tree cover of the HGs to control the conversion and to restore ecological services.DOI: http://doi.org/10.31357/fhss/vjhss.v06i01.0

Backstepping control of three-phase three-level four-leg shunt active power filter

In this paper, backstepping control for three-level four-leg shunt active power filter (SAPF) system is proposed. The adopted filtering topology requires both a three-dimensional space vector modulation (3DSVM) for controlling the three-level four-leg inverter as well as DC voltage and filter currents control. The regulation of the DC voltage and filter currents is accomplished by backstepping controllers. The voltage-balancing control of two split DC capacitors of the three-level four-leg SAPF is achieved using three-level three-dimensional space vector modulation equipped by a balancing strategy based on the effective use of the redundant switching states of the inverter voltage vectors. The simulation results show the effectiveness of the proposed filtering system in terms of the compensation of the harmonics and the zero sequence current and the operation at unity power factor.Keywords: shunt active power filter; three-dimensional space vector modulation; multilevel four-leg inverter; backstepping control; synchronous reference frame theory

Predatory ability of generalist predators on eggs, young nymphs and adults of the invasive Halyomorpha halys in southern Europe

Halyomorpha halys (Stål, 1855) is an invasive pest causing serious damage to agricultural crops in Europe and the USA. Very little is known about H. halys predators in Europe. This survey evaluated the potential of generalist predators/omnivorous species by means of predation bioassays in tri-dimensional arenas, where the predator had to locate H. halys prey items on the leaves of a bean plant. Eleven species of different taxa were tested and the prey items consisted in fresh eggmasses, 1st and 2nd instar nymphs. One species was also tested against adults. Some predators were species commercially available as biocontrol agents against plant pests, other predators were wild, captured in habitats shared with H. halys. All tested specimens were starved 24 h before starting the experiment. The survivorship of control prey items in predator-excluding cages was compared to that of predator treatment groups to determine the effect of predator presence. According to the results, the generalist species showed a quite low acceptance of H. halys prey items, since only two species caused 80% mortality on at least one item (Eupholidoptera chabrieri and Rhynocoris iracundus) and mortality due the other species never exceed 60%. Among commercially available species only Adalia bipunctata adults and Chrysoperla carnea larvae were effective, predating the eggs and 1st instar nymphs, respectively. Among the field collected specimens, the orthopteran E. chabrieri and the predatory hemipterans R. iracundus, Nagusta goedelii and Himacerus mirmicoides showed efficacy against 1st instar nymphs, E. chabrieri and R. iracundus showed efficacy against 2nd instar nymphs, whereas only E. chabrieri and N. goedelii predated the eggs. R. iracundus was also tested on the adults and successfully predated them. By identifying some of the species that can exploit H. halys as a suitable prey in southern Europe, the present investigation provides an important contribution for conservation biological control of this pest

Reactive power control to enhance the VSC-HVDC system performance under faulty and normal conditions

This paper studied the reactive power control of the voltage source converters based high-voltage direct current system (VSC-HVDC). PI (proportional & integration) controller was used in this work to enhance the dynamic response of the system. Gravitational search algorithm (GSA) and sine cosine algorithm (SCA) are used to get optimal parameters of the PI controller. GSA algorithm is based on the gravity law for Newton while SCA depends on mathematical model based on cosine and sine functions. These algorithms have an efficient global Search capability. The VSC-HVDC is exposed to different disturbances for checking the controller robustness. First disturbance was applying three phase faults on the system. While the second one was applying a step change in AC voltage. Finally, Applying step change in regulators reference values. Simulation results proved the controller superiority also verified the enhancement of the system dynamic response

Integrative network analysis identified key genes and pathways in the progression of hepatitis C virus induced hepatocellular carcinoma

Background: Incidence of hepatitis C virus (HCV) induced hepatocellular carcinoma (HCC) has been increasing in the United States and Europe during recent years. Although HCV-associated HCC shares many pathological characteristics with other types of HCC, its molecular mechanisms of progression remain elusive. Methods: To investigate the underlying pathology, we developed a systematic approach to identify deregulated biological networks in HCC by integrating gene expression profiles with high-throughput protein-protein interaction data. We examined five stages including normal (control) liver, cirrhotic liver, dysplasia, early HCC and advanced HCC. Results: Among the five consecutive pathological stages, we identified four networks including precancerous networks (Normal-Cirrhosis and Cirrhosis-Dysplasia) and cancerous networks (Dysplasia-Early HCC, Early-Advanced HCC). We found little overlap between precancerous and cancerous networks, opposite to a substantial overlap within precancerous or cancerous networks. We further found that the hub proteins interacted with HCV proteins, suggesting direct interventions of these networks by the virus. The functional annotation of each network demonstrates a high degree of consistency with current knowledge in HCC. By assembling these functions into a module map, we could depict the stepwise biological functions that are deregulated in HCV-induced hepatocarcinogenesis. Additionally, these networks enable us to identify important genes and pathways by developmental stage, such as LCK signalling pathways in cirrhosis, MMP genes and TIMP genes in dysplastic liver, and CDC2-mediated cell cycle signalling in early and advanced HCC. CDC2 (alternative symbol CDK1), a cell cycle regulatory gene, is particularly interesting due to its topological position in temporally deregulated networks. Conclusions: Our study uncovers a temporal spectrum of functional deregulation and prioritizes key genes and pathways in the progression of HCV induced HCC. These findings present a wealth of information for further investigation

Vulnerability of Brazilian municipalities to hantavirus infections based on multi‑criteria decision analysis

Background: Hantavirus infection is an emerging zoonosis transmitted by wild rodents. In Brazil, high case-fatality rates among humans infected with hantavirus are of serious concern to public health authorities. Appropriate preventive measures partly depend on reliable knowledge about the geographical distribution of this disease. Methods: Incidence of hantavirus infections in Brazil (1993–2013) was analyzed. Epidemiological, socioeconomic, and demographic indicators were also used to classify cities’ vulnerability to disease by means of multi-criteria decision analysis (MCDA). Results: From 1993 to 2013, 1752 cases of hantavirus were registered in 16 Brazilian states. The highest incidence of hantavirus was observed in the states of Mato Grosso (0.57/100,000) and Santa Catarina (0.13/100,000). Based on MCDA analysis, municipalities in the southern, southeastern, and midwestern regions of Brazil can be classified as highly vulnerable. Most municipalities in northern and northeastern Brazil were classified as having low vulnerability to hantavirus cardiopulmonary syndrome. Conclusions: Although most human infections by hantavirus registered in Brazil occurred in the southern region of the country, a greater vulnerability to hantavirus was found in the Brazilian Midwest. This result reflects the need to strengthen surveillance where the disease has thus far gone unreported

An improved prediction of pre-combustion processes, using the discrete multi-component model

An improved heating and evaporation model of fuel droplets is implemented into the commercial Computational Fluid Dynamics (CFD) software CONVERGE for the simulation of sprays. The analytical solutions to the heat conduction and species diffusion equations in the liquid phase for each time step are coded via user-defined functions (UDF) into the software. The customized version of CONVERGE is validated against measurements for a single droplet of n-heptane and n-decane mixture. It is shown that the new heating and evaporation model better agrees with the experimental data than those predicted by the built-in heating and evaporation model, which does not consider the effects of temperature gradient and assumes infinitely fast species diffusion inside droplets. The simulation of a hollow-cone spray of primary reference fuel (PRF65) is performed and validated against experimental data taken from the literature. Finally, the newly implemented model is tested by running full-cycle engine simulations, representing partially premixed compression ignition (PPCI) using PRF65 as the fuel. These simulations are successfully performed for two start of injection timings, 20 and 25 crank angle (CA) before top-dead-centre (BTDC). The results show good agreement with experimental data where the effect of heating and evaporation of droplets on combustion phasing is investigated. The results highlight the importance of the accurate modelling of physical processes during droplet heating and evaporation for the prediction of the PPCI engine performance

Chemical Kinetic Insights into the Octane Number and Octane Sensitivity of Gasoline Surrogate Mixtures

Gasoline octane number is a significant empirical parameter for the optimization and development of internal combustion engines capable of resisting knock. Although extensive databases and blending rules to estimate the octane numbers of mixtures have been developed and the effects of molecular structure on autoignition properties are somewhat understood, a comprehensive theoretical chemistry-based foundation for blending effects of fuels on engine operations is still to be developed. In this study, we present models that correlate the research octane number (RON) and motor octane number (MON) with simulated homogeneous gas-phase ignition delay times of stoichiometric fuel/air mixtures. These correlations attempt to bridge the gap between the fundamental autoignition behavior of the fuel (e.g., its chemistry and how reactivity changes with temperature and pressure) and engine properties such as its knocking behavior in a cooperative fuels research (CFR) engine. The study encompasses a total of 79 hydrocarbon gasoline surrogate mixtures including 11 primary reference fuels (PRF), 43 toluene primary reference fuels (TPRF), and 19 multicomponent (MC) surrogate mixtures. In addition to TPRF mixture components of iso-octane/n-heptane/toluene, MC mixtures, including n-heptane, iso-octane, toluene, 1-hexene, and 1,2,4-trimethylbenzene, were blended and tested to mimic real gasoline sensitivity. ASTM testing protocols D-2699 and D-2700 were used to measure the RON and MON of the MC mixtures in a CFR engine, while the PRF and TPRF mixtures' octane ratings were obtained from the literature. The mixtures cover a RON range of 0-100, with the majority being in the 70-100 range. A parametric simulation study across a temperature range of 650-950 K and pressure range of 15-50 bar was carried out in a constant-volume homogeneous batch reactor to calculate chemical kinetic ignition delay times. Regression tools were utilized to find the conditions at which RON and MON best correlate with simulated ignition delay times. Furthermore, temperature and pressure dependences were investigated for fuels with varying octane sensitivity. This analysis led to the formulation of correlations useful to the definition of surrogates for modeling purposes and allowed one to identify conditions for a more in-depth understanding of the chemical phenomena controlling the antiknock behavior of the fuels

TFC056 Effect of cell penetrating peptide (TAT) on the complexation and transfection of siRNA

Gene therapy has been investigated as a strategy for the treatment of numerous diseases, such as cancer, AIDS and cystic fibrosis. In this way, post-transcriptional gene silencing by RNA interference rises as an interesting method for the target inhibition of gene expression. It should be emphasized the potential to specifically and potently knock down gene expression, however, naked siRNAs cannot reach the intracellular environment due to its high molecular weight and strongly negative charge. Then, considerable research effort is currently focused on the development of safe and effective delivery systems for these promising molecules

Morphometry-based radiomics for predicting therapeutic response in patients with gliomas following radiotherapy

IntroductionGliomas are still considered as challenging in oncologic management despite the developments in treatment approaches. The complete elimination of a glioma might not be possible even after a treatment and assessment of therapeutic response is important to determine the future course of actions for patients with such cancers. In the recent years radiomics has emerged as a promising solution with potential applications including prediction of therapeutic response. Hence, this study was focused on investigating whether morphometry-based radiomics signature could be used to predict therapeutic response in patients with gliomas following radiotherapy.Methods105 magnetic resonance (MR) images including segmented and non-segmented images were used to extract morphometric features and develop a morphometry-based radiomics signature. After determining the appropriate machine learning algorithm, a prediction model was developed to predict the therapeutic response eliminating the highly correlated features as well as without eliminating the highly correlated features. Then the model performance was evaluated.ResultsTumor grade had the highest contribution to develop the morphometry-based signature. Random forest provided the highest accuracy to train the prediction model derived from the morphometry-based radiomics signature. An accuracy of 86% and area under the curve (AUC) value of 0.91 were achieved for the prediction model evaluated without eliminating the highly correlated features whereas accuracy and AUC value were 84% and 0.92 respectively for the prediction model evaluated after eliminating the highly correlated features.DiscussionNonetheless, the developed morphometry-based radiomics signature could be utilized as a noninvasive biomarker for therapeutic response in patients with gliomas following radiotherapy