bluuebunny/crossref_metadata_2025 huggingface dataset:
Life Cycle Assessment of Solar Façade Concepts Based on Transparent Insulation Materials
Authors: Struhala Karel , Čekon Miroslav , Slávik Richard
Published: November 2018

Contemporary architects and the construction industry are trying to cope with increasing requirements concerning energy efficiency and environmental impact. One of the available options is the active utilization of energy gains from the environment, specifically solar energy gains. These gains can be utilized by, for example, solar walls and facades. The solar façade concept has been under development for more than a century. However, it hasn’t achieved widespread use for various reasons. Rather recently the concept was enhanced by the application of transparent insulation materials that have the potential to increase the efficiency of such façades. The presented study evaluates the environmental efficiency of 10 solar façade assemblies in the mild climate of the Czech Republic, Central Europe. The evaluated façade assemblies combine the principles of a solar wall with transparent insulation based on honeycomb and polycarbonate panels. The study applies Life-Cycle Assessment methodology to the calculation of environmental impacts related to the life cycle of the evaluated assemblies. The results indicate that even though there are several limiting factors, façade assemblies with transparent insulation have lower environmental impacts compared to a reference assembly with standard thermal insulation. The highest achieved difference is approx. 84% (in favour of the assembly with transparent insulation) during a modelled 50-year façade assembly service life.
Oleuropein, the Main Polyphenol of Olea europaea Leaf Extract, Has an Anti Cancer Effect on Human BRAF Melanoma Cells and Potentiates the Cytotoxicity of Current Chemotherapies
Authors: Ruzzolini Jessica , Peppicelli Silvia , Andreucci Elena , Bianchini Francesca , Scardigli Arianna , Romani Annalisa , LaMarca Giancarlo , Nediani Chiara , Calorini Lido
Published: November 2018

Oleuropein (Ole), a secoiridoid glucoside present in Olea europaea leaves, gained the interest of many scientists thanks to its several biological properties, including the anticancer one. We verified whether Ole might potentiate cytotoxicity of conventional drugs used to treat melanoma, disclosing new potential therapeutic strategy. We tested the cytotoxic action of Ole alone or in combination with chemotherapeutics on A375 human melanoma cells. We found that Ole was able, at a dose of 500 μM, to stimulate apoptosis in melanoma cells, while at a non-toxic dose of 250 μM, it affected cell proliferation and induced the downregulation of pAKT/pS6 pathway. 250 μM Ole did not potentiate the effect of Vemurafenib (PLX4032), but it succeeded in increase the cytotoxic effect of Dacarbazine (DTIC). The mayor effect was found in the association between Ole and Everolimus (RAD001), also on PLX4032-resistant BRAF melanoma cells, possibly cooperating in the inhibition of pAKT/pS6 pathway. Of interest, an olive leaf extract enriched in equimolar Ole was more effective and able to further improve DTIC and, particularly, RAD001 efficacy on BRAF melanoma cells than Ole alone. Therefore, Ole represents a natural product able to potentiate a wide array of chemotherapeutics against BRAF melanoma cells affecting pAKT/pS6 pathway.
SN1 Transporter Regulation by Sp1 in Ammonia-Treated Mouse Cortical Astrocytes: Role of Sp1 Phosphorylation Status
Authors: Dąbrowska Katarzyna , Zielińska Magdalena
Published: November 2018

The involvement of astrocytic SN1 (SNAT3) transporter in ammonia-induced L-glutamine retention was recently documented in mouse cultured astrocytes. Here we investigated the involvement of specificity protein 1 (Sp1) transcription factor in SN1 regulation in ammonium chloride (“ammonia”)-treated astrocytes. Sp1 expression and its cellular localization were determined using real-time qPCR, Western blot and confocal microscopy, respectively. Sp1 binding to Snat3 promoter was analyzed by chromatin immunoprecipitation. Ammonia-induced Sp1 regulatory role in SN1-mediated [3H]glutamine transport was verified using siRNA and mithramycin A. The involvement of protein kinase C (PKC) isoforms in Sp1 level/phosphorylation status was verified using siRNA technology. Sp1 translocation to the nuclei and its enhanced binding to Snat3 promoter, along with Sp1 dependence of system N-mediated [3H]glutamine transport were observed in astrocytes upon ammonia exposure. Ammonia decreased the level of phosphorylated Sp1, and the effect was reinforced by long-term incubation with PKC modulator, phorbol 12-myristate 13-acetate, a treatment likely to dephosphorylate Sp1. Furthermore,  silencing of PKCδ isoform abolished the increase of Sp1 level by ammonia. Collectively, the results demonstrate the regulatory role of Sp1 in regulation of SN1 expression and activity in ammonia-treated astrocytes and implicate altered Sp1 phosphorylation status in this capacity.
Starch Degradability of Maize Kernels as Influenced by Type of Endosperm and Soil in Rumen Fluid at Different Maturity Stages
Authors: Ali Mazhar , Cone John W. , Hendriks Wouter H. , Javeed Hafiz Muhammad Rashad , Qamar Rafi , Khan Mubrak ALi , Struik Paul C.
Published: November 2018

Starch is considered a major nutritional factor of maize (Zea mays L.) kernels, and can be influenced by the type of endosperm. The effects of endosperm type (vitreous and non-vitreous) and type of soil (clay and sand) on the starch content of kernels of maize, and on the in vitro degradation of starch were investigated in the rumen fluid after harvesting at 6 different maturity stages during 2008 and five different maturity stages in 2009. Starch degradation, in rumen fluid, was determined after 6 h, 12 h and 20 h of incubation, using the technique of gas production. A positive linear relationship was observed during gas production (ml gas/g organic matter) and starch degradation (g kg-1 starch) at all incubation times, with starch contents of maize kernels to a certain limit of starch accumulation (i.e. at starch contents 451-519 g/kg OM) and negative relationship afterwards. This suggests significant effects of maturity on ruminal starch degradation of maize kernels. At each harvest date, ruminal starch degradation of maize kernels was affected by crop genotype as well as soil type. The in vitro ruminal degradation potential of starch in maize kernels was influenced by the nature of the endosperm, with a higher degradation of non-vitreous kernels than of vitreous kernels. The rumen starch degradation was also influenced by type of soil, with better degradation on clay than sandy soil. For all the incubation times and maturity stages the effects of genotype, soil type and maturity stage were consistent in rumen fluid.
Greenhouse Soil Biosolarization with Tomato Plant Debris as Unique Fertilizer for Tomato Crops
Authors: García-Raya Pablo , Ruiz-Olmos César , Marín-Guirao José Ignacio , Asensio-Grima Carlos , Tello-Marquina Julio César , de Cara-García Miguel
Published: November 2018

Intensive greenhouse horticulture can cause various environmental problems. Among them, the management, storage and processing of crop residues can provoke aquifer contamination, pest proliferation, bad odors or the abuse of phytosanitary treatments. Biosolarization put in value any fresh plant residue and is an efficient technique for the control of soil-borne diseases. This study aims to examine an alternative means of managing greenhouse crop residues through biosolarization and to investigate the influence of organic matter on yield and quality of tomato (Solanum lycopersicum, L.) fruit. With this purpose, the following nutritional systems were evaluated: inorganic fertilization with and without brassica pellets (Fert, Fert + and Fert ++), fresh tomato plant debris with and without brassica pellets (Rest, Rest + and Rest ++) and no fertilizer application (Control). The addition of organic matter equaled all the treatments except for control with regard to yield and quality of the tomato fruit. In light of these results, the application of tomato plant debris to the soil through biosolarization is postulated as an alternative for the management of crop residues, solving an environmental problem and having a favorable impact on the production and quality of tomatoes as a commercial crop.
Predicting Heat Meters’ Failures With Selected Machine Learning Models
Authors: Pałasz Przemysław , Przysowa Radosław
Published: November 2018

Heat metres are used to calculate the consumed energy in central heating systems. The subject of this article is to prepare a method of predicting a failure of a heat meter in the next settlement period. Predicting failures is essential to coordinate the process of exchanging the heat metres and to avoid inaccurate readings, incorrect billing and additional costs. The reliability analysis of heat metres was based on historical data collected over many years. Three independent models of machine learning were proposed, and they were applied to predict failures of metres. The efficiency of the models was confirmed and compared using the selected metrics. The optimisation of hyperparameters characteristics for each of models was successfully applied. The article shows that the diagnostics of devices does not have to rely only on newly collected information, but it is also possible to use the existing big data sets.
Entropy and Mutability for the Q-States Clock Model in Small Systems
Authors: Negrete Oscar A. , Vargas Patricio , Peña Francisco J. , Saravia Gonzalo , Vogel Eugenio E.
Published: November 2018

In this paper, we revisit the q-states clock model for small systems. We present results for the thermodynamics of the q-states clock model from $q=2$ to $q=20$ for small square lattices $L \times L$, with L ranging from $L=3$ to $L=64$ with free-boundary conditions. Energy, specific heat, entropy and magnetization are measured. We found that the Berezinskii-Kosterlitz-Thouless (BKT)-like transition appears for $q>5$ regardless of lattice size, while the transition at $q=5$ is lost for $L<10$; for $q\leq 4$ the BKT transition is never present. We report the phase diagram in terms of $q$ showing the transition from the ferromagnetic (FM) to the paramagnetic (PM) phases at a critical temperature T$_1$ for small systems which turns into a transition from the FM to the BKT phase for larger systems, while a second phase transition between the BKT and the PM phases occurs at T$_2$. We also show that the magnetic phases are well characterized by the two dimensional (2D) distribution of the magnetization values. We make use of this opportunity to do an information theory analysis of the time series obtained from the Monte Carlo simulations. In particular, we calculate the phenomenological mutability and diversity functions. Diversity characterizes the phase transitions, but the phases are less detectable as $q$ increases. Free boundary conditions are used to better mimic the reality of small systems (far from any thermodynamic limit). The role of size is discussed.
Development of a Transformation Method for Metschnikowia borealis and Other CUG-Serine Yeasts
Authors: Gordon Zachary , Soltysiak Maximillian P. M. , Leichthammer Christopher , Therrien Jasmine A. , Meaney Rebecca S. , Lauzon Carolyn , Adams Matthew , Lee Dong Kyung , Janakirama Preetam , Lachance Marc-Andre , Karas Bogumil J.
Published: November 2018

Yeasts belonging to the Metschnikowia genus are particularly interesting for the unusual formation of only two needle-shaped ascospores during their mating cycle. Presently, the meiotic process that can lead to only two spores from a diploid zygote is poorly understood. The expression of fluorescent nuclear proteins should allow the meiotic process to be visualized in vivo; however, no large-spored species of Metschnikowia has ever been transformed. Accordingly, we aimed to develop a transformation method for Metschnikowia borealis, a particularly large-spored species of Metschnikowia, with the goal of enabling the genetic manipulations required to study biological processes in detail. Genetic analyses confirmed that M. borealis, and many other Metchnikowiacea, are CUG-Ser yeasts. Codon-optimized selectable markers lacking CUG codons were used to successfully transform M. borealis by electroporation and lithium acetate, and transformants appeared to be the result of random integration. Mating experiments confirmed that transformed-strains were capable of generating large asci and undergoing recombination. Finally, random integration was used to transform an additional 18 yeast strains, and all attempts successfully generated transformants. The results provide a simple method to transform many yeasts from an array of different clades and can be used to study or develop many species for various applications.
NLP Formulation for Polygon Optimization Problems
Authors: Asaeedi Saeed , didehvar farzad , Mohades Ali
Published: November 2018

In this paper, we generalize the problems of finding simple polygons with the minimum area, maximum perimeter and maximum number of vertices so that they contain a given set of points and their angles are bounded by $\alpha+\pi$ where $\alpha$ ($0\leq\alpha\leq \pi$) is a parameter. We also consider the maximum angle of each possible simple polygon crossing a given set of points, and derive an upper bound for the minimum of these angles. The correspondence between the problems of finding simple polygons with the minimum area and maximum number of vertices is investigated from a theoretical perspective. We formulate the three generalized problems as nonlinear programming models, and then present a Genetic Algorithm to solve them. Finally, the computed solutions are evaluated on several datasets and the results are compared with those from the optimal approach.
Integration of Support Vector Regression With Distributed Gauss-Newton Optimization Method and Its Applications to the Uncertainty Assessment of Unconventional Assets
Authors: Guo Zhenyu , Chen Chaohui , Gao Guohua , Cao Richard , Li Ruijian , Liu Chunlei
Published: November 2018

Reservoir model parameters generally have very large uncertainty ranges, and need to be calibrated by history matching (HM) available production data. Properly assessing the uncertainty of production forecasts (e.g., with an ensemble of calibrated models that are conditioned to production data) has a direct impact on business decision making. It requires performing numerous reservoir simulations on a distributed computing environment. Because of the current low-oil-price environment, it is demanding to reduce the computational cost of generating multiple realizations of history-matched models without compromising forecasting quality. To solve this challenge, a novel and more efficient optimization method (referred to as SVR-DGN) is proposed in this paper, by replacing the less accurate linear proxy of the distributed Gauss-Newton (DGN) optimization method (referred to as L-DGN) with a more accurate response-surface model of support vector regression (SVR).

Resembling L-DGN, the proposed SVR-DGN optimization method can be applied to find multiple local minima of the objective function in parallel. In each iteration, SVR-DGN proposes an ensemble of search points or reservoir-simulation models, and the flow responses of these reservoir models are simulated on high-performance-computing (HPC) clusters concurrently. All successfully simulated cases are recorded in a training data set. Then, an SVR proxy is constructed for each simulated response using all training data points available in the training data set. Finally, the sensitivity matrix at any point can be calculated analytically by differentiating the SVR models. SVR-DGN computes more-accurate sensitivity matrices, proposes better search points, and converges faster than L-DGN.

The quality of the SVR proxy is validated with a toy problem. The proposed method is applied to a real field HM example of a Permian liquid-rich shale reservoir. The uncertain parameters include reservoir static properties, hydraulic-fracture properties, and parameters defining relative permeability curves. The performance of the proposed SVR-DGN optimization method is compared with the L-DGN optimizer and the hybrid Gauss-Newton with a direct-pattern-search (GN-DPS) optimizer, using the same real field example. Our numerical tests indicate that the SVR-DGN optimizer can find better solutions with smaller values of the objective function and with a less computational cost (approximately one-third of L-DGN and 1/30 of GN-DPS). Finally, the proposed method is applied to generate multiple conditional realizations for the uncertainty quantification of production forecasts.
Sampling a Stimulated Rock Volume: An Eagle Ford Example
Authors: Raterman Kevin T. , Farrell Helen E. , Mora Oscar S. , Janssen Aaron L. , Gomez Gustavo A. , Busetti Seth , McEwen Jamie , Friehauf Kyle , Rutherford James , Reid Ray , Jin Ge , Roy Baishali , Warren Mark
Published: November 2018

Between 2014 and 2016, ConocoPhillips drilled five deviated wells adjacent to a multistage, stimulated horizontal producer to sample the physical characteristics of the reservoir stimulation caused by hydraulic fracturing in the Eagle Ford Formation in DeWitt County, Texas. The design, execution, and results of the pilot are described. This pilot establishes the paucity of pre-existing natural fractures in this locale and enables the determination of the spatial characteristics of the stimulation using information derived from the core, cuttings samples, borehole-image logs, tracer logs, microseismic, distributed temperature sensing (DTS)/distributed acoustic sensing (DAS), and pressure data. Results show that stimulation effectively breaks the reservoir rock and makes a complex array of hydraulic fractures that are more closely spaced near the producer. Some fractures, however, extend interwell distances of more than 1,000 ft. The pilot data indicate that abundant proppant transport appears to be limited to distances less than 75 ft from the producer, which suggests that the stimulated rock volume (SRV) might be greater than the volume of rock that can be effectively drained.
Case Study for Early Design Optimization of Fatigue Sensitive Tubular Connections in Fixed Offshore Platforms
Authors: Khalil Ahmed , Agrawal Rajender , Kamal Faris , Takieddine Oussama
Published: November 2018

Members forming part of structures exposed to cyclic loading (such as offshore oil and gas platforms) are engineered to satisfy various pre-service and in-service loading conditions which include being checked for compliance with fatigue design requirements. In this study, the parameters that affect welded tubular joint fatigue performance are identified to assist design engineers achieve a preliminary design that is more likely to satisfy the fatigue design requirements early in the design cycle with the aim of avoiding later changes in the design.

State-of-the-art Finite Element modelling techniques were implemented throughout the course of this study. For a selected typical K-T joint from a 3D support frame ‘Study Model’ initially created in SACS (Structural Analysis Computer Software) was replicated in ANSYS and variations in Stress Concentation Factor (SCF), Hot Spot Stress (HSS) and fatigue life were studied with respect to variable joint properties, namely brace to chord diameter ratio (d/D), brace to chord thickness ratio (t/T) and brace diameter to thickness ratio (d/t). Results obtained from both programs were compared as means for validation of study model. Following the validation process, the same principles were applied to the Case Study.

The Study Model - found a good correlation between the trend of variation of results obtained from Nominal Stress Approach and Hot Spot Stress Approach. This serves the purpose of validating the Nominal Stress Approach methodology which shall then be used in the Case Study.

Case Study- Fixed Offshore Platform- Fatigue Life predicted longer for joints with d/D in the range 0.41 to 0.44 for constant member combined stress utilization ratio (UCR) and constant t/T. Fatigue Life predicted longer for joints with t/T in the range 0.345 to 0.375 for constant member UCR and constant d/D. Fatigue Life predicted longer for joints with d/t in the range 28 to 36 for constant member UCR, constant d/D and constant t/T.

Engineering Consultants and EPC Contractors executing projects involving detailed engineering through to installation of fixed offshore platforms perform structural analysis to define material requirements. Performing fatigue analyses for the final outcome of static in-service analysis may result in re-sizing of members during the course of the design cycle. The joint parameters derived by this paper can be applied at an early stage of the design process with the aim of confidently defining sizing of tubular joints that are likely to satisfy fatigue design requirements. This greatly enhances engineering efficiency by avoiding later design changes in the design cycle.
Variable Exponential Decline: Modified Arps To Characterize Unconventional-Shale Production Performance
Authors: Gupta Ishank , Rai Chandra , Sondergeld Carl , Devegowda Deepak
Published: November 2018

Different decline-curve-analysis (DCA) methods have been proposed to predict the production performance of both conventional and unconventional-shale reservoirs. These methods range from empirical to semiempirical and theoretical. The different methods were developed using specific data sets and have their own assumptions and limitations, and thus are not universally applicable.

This study shows that a DCA method should be capable of simultaneously modeling the flow regime prevalent around the well and the changes in reservoir properties with time, to be able to successfully represent the production performance of the well and predict future performance. In shales, flow regimes can be linear, bilinear, multifracture linear, post-linear, stimulated-reservoir-volume (SRV) -dominated boundary flow, or compound linear. The change in fracture conductivity caused by fines migration, embedment, crushing, diagenesis, and change in stresses because of production is another important phenomenon for which a DCA method must account.

This study critically analyzes various proposed historical DCA methods with respect to their capability to model fracture-flow regimes and changes in fracture conductivity with time. Upon close examination, it was found that both the linear-flow regimes and changes in fracture conductivity with time follow a power-law function. Thus, the reason for the successful application of the Arps (1944) hyperbolic, power-law-exponential (PLE), stretched-exponential-decline (SEPD), and Duong (2010) methods is that decline rates in these methods are a power-law function or can be closely approximated by a power-law function.

A new simplified decline-curve equation is proposed by modifying the existing Arps exponential-decline equation, where the constant-decline rate is replaced by a power-law-function variable decline rate. The application of this method is shown using production data from Haynesville Formation and Eagle Ford Formation shales. The average error in cumulative-production prediction for 20 wells was found to be only 3% in Haynesville wells and 2% in Eagle Ford wells. This method is very robust and can account for different flow regimes and changes in fracture conductivity with time.
A New Workflow for Improved Water-Saturation Assessment in Organic-Rich Mudrocks Honoring Rock Fabric
Authors: Garcia Artur Posenato , Heidari Zoya , Rostami Ameneh
Published: November 2018

The complexity of rock fabric (e.g., spatial distribution of pores and rock components) in organic-rich mudrocks has a significant impact on rock properties, such as electrical resistivity, and hence on estimates of hydrocarbon reserves. Actual spatial distributions of pores and rock components are not accounted for in conventional petrophysical models. For instance, clays are typically considered to be distributed in laminated, dispersed, or structural forms. However, clay distribution in organic-rich mudrocks might not fit any of these categories. Furthermore, conventional models do not incorporate conductive components—other than brine and clay minerals—in interpretation of resistivity measurements. We introduce a new resistivity-based workflow that quantitatively assimilates the type and the spatial distribution of all conductive components to improve reserves evaluation. To achieve this objective, we (a) introduce a directional connectivity parameter that quantifies the influence of clay, kerogen, pyrite, and brine network connectivity on electrical resistivity; (b) develop a new method that relates electrical resistivity to directional connectivity of all the conductive components; and (c) improve the estimates of water saturation in organic-rich mudrocks.

The new resistivity method incorporates directional connectivity of each conductive component of the rock. This parameter is a function of rock-fabric features such as directional tortuosity and constriction factor of each component. The aforementioned features are quantified using focused-ion-beam scanning-electron-microscope (FIB-SEM) 3D pore-scale images. We apply a semianalytical streamline model to estimate the network connectivity of the conductive components, which will be inputs to the new workflow. We successfully applied the new method to pore-scale rock samples from one organic-rich mudrock formation and several synthetic cases. The results of numerical simulations showed that the sensitivity of electrical conductivity to spatial distribution of conductive components can be significant, depending on their volumetric concentration and electrical properties. Finally, comparison of the new method against a conventional method [i.e., the Waxman-Smits model (Waxman and Smits 1968)] showed that water saturation can be improved by up to 35% when a quantitative and realistic spatial distribution of all the conductive components (e.g., pyrite, clay, and kerogen) is taken into account.
Competitive Indices in Cereal and Legume Mixtures in a South Asian Environment
Authors: Iqbal Muhammad Aamir , Hamid Abdul , Hussain Imtiaz , Siddiqui Muzammil H. , Ahmad Tanveer , Khaliq Abdul , Ahmad Zahoor
Published: November 2018

Core Ideas

Cereal‐legume binary mixtures increased forage productivity per unit area compared to cereal‐cereal and legume‐legume binary mixtures.

In binary mixtures, pearl millet was marginally more resistant to yield reduction in comparison to sorghum.

Soybean suffered the highest yield losses in binary mixtures compared to cowpea and cluster bean.

The assessment of competitive performance of mixture components is important for maximizing benefits of intercropping systems. This field study tested binary mixtures of two cereals {sorghum [Sorghum bicolor (L.) Moench] and pearl millet [Cenchrus americanus (L.) Morrone]} and three forage legumes {cowpea [Vigna unguiculata (L.) Walp.], cluster bean [Cyamopsis tetragonoloba (L.) Taub.], and soybean[Glycine max (L.) Merr.]}, along with their sole crops on competitive indices. Sorghum–cowpea binary mixture resulted in a lower green forage yield of sorghum and cowpea by 9 and 36%, respectively, but overall biomass production was increased by 30 and 117% compared to their sole crop equivalents. Partial land equivalent ratios (LER) of all component crops were higher than 0.50, indicating better land use efficiency, except of soybean in binary mixtures with cowpea and cluster bean. However, the highest LER was of sorghum–cowpea (1.55), followed by sorghum–soybean (1.48) and pearl millet–soybean (1.48) binary mixtures. Pearl millet dominated sorghum and all legumes, while cowpea remained a superior competitor among legumes as per aggressivity value (AV) index. The highest crowding ratio (CR) was exhibited by pearl millet in binary mixture with cluster bean indicating its higher competitive ability in comparison to other mixture components. Observed yield loss data indicated that pearl millet was the most resistant crop to yield loss in all binary mixtures, while soybean had the highest yield reduction. In a short term, the highest area time equivalent ratio (ATER) for sorghum–cowpea binary mixture indicated the maximum advantage for this binary mixture compared to other binary mixtures.
Filtering of Periodic Infiltration in a Layered Vadose Zone: 2. Applications and a Freeware Screening Tool
Authors: Dickinson Jesse E. , Ferré T.P.A.
Published: November 2018

Core Ideas

Infiltration forcings are filtered (time lagged and damped) with increasing depth.

Filtering generally increases with increasing infiltration and cycle period.

We show where forcings can produce variable recharge in Central Valley (California).

We have developed a screening tool to visualize and conceptualize the filtering properties of a layered vadose zone. Climate projections indicate that rainfall timing and magnitude may change and impact groundwater resources. This increases the importance of understanding how the vadose zone filters infiltration variability and ultimately affects recharge and groundwater resources. An approximate solution for the filtering of surface forcings through soil layers was developed previously, and the soil and conditions where its approximations are appropriate was evaluated. Here we present a screening tool based on the solution for estimating how periodic infiltration forcings filter in a layered vadose zone for different soil properties and surface flux conditions. The solutions identify time‐varying elements of surface forcings that persist to the depth of the water table, leading to transient recharge. We investigated the filtering properties of the vadose zone in Central Valley, California, and identified areas where surface forcings are essentially damped and recharge can be approximated as steady. We also determined the travel time for infiltration pulses to reach the depth of the water table.
Rational choice of antibacterial drug for the treatment of ent organs in outpatient practice
Authors: Eremin S. A. , Ryazantsev S. V. , Konoplev O. I.
Published: November 2018

The article examines the choice of a group of antibacterial drugs for the treatment of ENT organs with uncomplicated infections in the practice of the otorhinolaryngologist. Described the principles of antibacterial therapy, resistance of the main pathogens of infections of ENT organs (Streptococcus pneumonia, Streptococcus pyogenes, Haemophilus influenza, Moraxella catarrhalis) to antibiotics of different groups: penicillins, cephalosporins of different generations, macrolides, respiratory fluoroquinolones. It is told about the patient’s compliance to the prescribed treatment, which has a great influence not only on the effectiveness of treatment, but also on the increase of antibiotic resistance in general. A group of cephalosporins of the third generation for oral administration (Cefixime) has some competitive advantages over other groups antibiotics: better adherence like as macrolides and high susceptibility of a wide range of bacteria, like as penicillins and fluoroquinolones.
Adsorption of phosphorus with calcium alginate beads containing drinking water treatment residual
Authors: Shen Cheng , Zhao Yaqian , Liu Ranbin , Mao Yi , Morgan David
Published: November 2018

Aluminum-based drinking water treatment residuals (DWTR) were encapsulated by alginate to develop a pelletized media (DWTR-CA beads) for phosphorus (P) adsorption. The beads were successfully manufactured to uniform size and shape requirements. The effects of DWTR powder concentration and particle size, and bead mean size on P adsorption, were investigated. The DWTR was found to be an important component in the beads for P adsorption, while the calcium alginate shell contributed little for P adsorption. The maximum P adsorption capacity of the DWTR-CA bead was 19.42 mg P/g wet beads, corresponding to a bead diameter of 3.1 ± 0.2 mm and DWTR concentration of 2% (1% weight/volume (W/V)), mg/mL). The adsorption data fit well with the intra-particle diffusion model and the pseudo-second-order kinetic model, while both the Langmuir and Freundlich adsorption isotherms described the adsorption process well. Furthermore, the study on the effect of pH on P adsorption showed that acidic conditions resulted in a better P adsorption and the DWTR-CA beads have the function of pH neutralization. The findings of this study show that the DWTR-CA beads are a promising adsorbent/substrate for P removal.
Primera época - Año X, Número 30, enero-junio de 2009
Authors: De San Luis Revista de El Colegio
Published: November 2018

Este número corresponde a la primera época de la Revista de El Colegio de San Luis, denominado VETAS.
Depression Assessment in Clinical Trials and Pre-clinical Tests: A Critical Review
Authors: Ferreira Miguel F. , Castanheira Lígia , Sebastião Ana M. , Telles-Correia Diogo
Published: November 2018

Depression is deeply rooted in human behavior. The development of new antidepressants demands
the creation of animal models to investigate new drugs, which potentially could work as antidepressants.
The aim of this review is to discuss the different ways of assessing depression in clinical research,
including clinical trials, and the different animal behavioral tests used to study depression and
test the efficacy of antidepressants in pre-clinical studies.

In clinical practice, a categorical classification, such as the Diagnostic and Statistical Manual of Mental
Disorders (DSM) and the International Statistical Classification of Diseases and Related Health Problems
(ICD) can be used for diagnosis, through the use of structured and semi-structured interviews. On
the other hand, depression can also be assessed using a dimensional approach, through self- or clinicianrated
questionnaires.

Regarding the assessment of the efficacy of antidepressants in animal models, several tests are routinely
used, namely the Forced Swim Test, the Modified Forced Swim Test, the Tail Suspension Test and the
Sucrose Preference Test. These tests are informative, providing that the following rules are taken into
account: 1) more than one test is used, with coherent results; 2) secondary drug effects, the most frequent
being putative changes in motor activity, are taken into account and properly controlled with specific
tests run concomitantly; 3) each test and specific protocol is validated with data from at least a gold
standard antidepressant drug. We herein briefly discuss the potential and limitations of each of those
tests.
Anxiety Assessment in Pre-clinical Tests and in Clinical Trials: A Critical Review
Authors: Castanheira Lígia , Ferreira Miguel F. , Sebastião Ana M. , Telles-Correia Diogo
Published: November 2018

The identification of anxious symptoms is crucial to diagnose anxiety disorders, as well as to
monitor their treatment in clinical practice and research. The aim of this review is to discuss the different
ways of assessing anxiety in clinical research, including clinical trials, and the different kinds of
animal behavioral tests used to study anxiety and test the efficacy of anxiolytics in pre-clinical studies.
In clinical practice, a categorical classification (such as the Diagnostic and Statistical Manual of Mental
Disorders and the International Statistical Classification of Diseases and Related Health Problems)
distinguishes the cases of the disease versus non-disease. Some structured and semi-structured
interviews can be used to arrive at these diagnoses. On the other hand, anxiety can also be assessed
using a dimensional approach, through self-report or hetero-evaluation questionnaires. Regarding the
assessment of anxiety in animals, several behavioral tests are described and evaluated, namely the
Social Interaction Test, Elevated Plus Maze and Open Field Test. Under a critical view, these two
approaches are presented and discussed, in order to improve the outcome of research in this field.
Potential Medicinal Applications of Vanadium and its Coordination Compounds in Current Research Prospects: A Review
Authors: Prasad Kollur S. , Ramachandrappa Shwetha U.
Published: November 2018

Background:

The variety of biological applications of vanadium impressed researchers to develop vanadium based drugs. The most well-known fact of vanadium is that it is necessary for human beings as an insulin-enhancing agent and herein, we mainly provide an overview of vanadium-based drugs and their applications in the medicinal field for the treatment of diseases such as diabetes and cancer. The first part of this review is focused on mechanistic studies involved in the anti-diabetic activity. The latter part explains the use of vanadium and its related coordination compounds in the treatment of cancer.

Methods:

This review is purely based on literature search available in the database. We focused on the reports available on the recent advancements in the vanadium chemistry and its biological properties, mainly anti-diabetic and anticancer activities of vanadium based compounds.

Results:

The study of clinical trials of vanadium and its drug molecules imposed more demand due to their remarkable activity with less toxicity.

Conclusion:

A brief literature survey was made pertaining to the applications of vanadium compounds/ complexes. Particularly, special attention was paid to explaining mechanistic studies of vanadium based compounds in the treatment of diabetes and cancer.
Synthesis of Polyaniline/Graphene Nanocomposites and Electrochemical Sensing Performance for Formaldehyde
Authors: Pei Lizhai , Ma Yue , Qiu Fanglv , Lin Feifei , Fan Chuangang , Ling Xianzhang
Published: November 2018

Background:

Formaldehyde has been recognized as the important liquid environmental
pollutant which can cause health risk. Great effort has been devoted to detecting formaldehyde in
liquid environment. It is of important significance to develop a sensitive method for measuring formaldehyde
from the environmental and health viewpoints.

Methods:

Polyaniline/graphene nanocomposites have been prepared by a simple in-situ polymerization
process using graphene and aniline as the raw materials. The nanocomposites were characterized
by Scanning Electron Microscopy (SEM), X-Ray Diffraction (XRD) and Transmission Electron Microscopy
(TEM) and high-resolution TEM (HRTEM). The polyaniline/graphene nanocomposites
were applied to modify the glassy carbon electrode for the detection of formaldehyde by cyclic voltammetry
(CV) method.

Results:

The polyaniline/graphene nanocomposites consist of hexagonal graphite phase. The polyaniline
particles are dispersed and attached to the surface of the graphene nanosheet-shaped morphology.
The thickness of the graphene nanosheets is less than 50 nm. The electrocatalytic performance
of the polyaniline/graphene nanocomposites modified glassy carbon electrode towards formaldehyde
was obtained. The potential of the irreversible oxidation peak is located at +0.19 V. The
polyaniline/graphene nanocomposites modified glassy carbon electrode shows a wide linear range of
0.0001-2 mM and low detection limit of 0.085 μM.

Conclusion:

The nanocomposites modified glassy carbon electrode possesses good reproducibility
and stability. The polyaniline/graphene nanocomposites show great application potential for the electrochemical
sensors to detect formaldehyde in liquid environments.
Improved Performance of CuFe2O4/rGO Nanohybrid as an Anode Material for Lithium-ion Batteries Prepared Via Facile One-step Method
Authors: Soomro Sumair Ahmed , Gul Iftikhar Hussain , Naseer Hashim , Marwat Shafiqullah , Mujahid Muhammad
Published: November 2018

Background: CuFe2O4 nanoparticles possess good electrochemical properties apart from
their inadequate electronic conductivity and large volume variation. The resulting performance lag
can be modified by the addition of conductive materials to form a composite. Hence, the properties
of CuFe2O4/rGO nanohybrid are presented for application as anode material for lithium-ion batteries.

Methods: The composites are synthesized through a facile one-step method of thermochemical reaction.
The samples are characterized by X-ray diffraction (XRD), Scanning Electron Microscope
(SEM), Fourier transform infrared spectroscopy (FTIR), Dielectric behavior and Galvanostatic
charge-discharge test.

Result & Conclusion: The XRD analysis confirmed the reduction of GO and formation of
CuFe2O4/rGO composite, whereas FTIR results showed two major vibrational bands that correspond
to spinel structure formation and attachment of rGO to CuFe2O4. The SEM images confirmed tethering
of CuFe2O4 nanoparticles with rGO sheets. It was also observed that the formation of the nanohybrid
of CuFe2O4 with rGO resulted in expected enhancement of the dielectric properties; dielectric
constant and AC conductivity. At 100 Hz frequency, the dielectric constant of the composite with 15
wt. % of GO was 1.27×105, which is higher than that of pure CuFe2O4 (3.57×104). The parameters
such as charge storage capacity and rate capability, which are reminiscent of battery performance
were also enhanced with the increase of rGO content in the composite. Hence, a substantial enhancement
of battery performance was depicted that projects the composite as a promising candidate
for applications in electrode material for lithium-ion batteries.
In-Silico Identification of Drug Lead Molecule Against Pesticide Exposed-neurodevelopmental Disorders Through Network-Based Computational Model Approach
Authors: Srivastava Neha , Mishra Bhartendu Nath , Srivastava Prachi
Published: November 2018

Background:

Neurodevelopmental Disorders (NDDs) are impairment of the growth and
development of the brain or central nervous system, which occurs at the developmental stage. This
can include developmental brain dysfunction, which can manifest as neuropsychiatric problems or
impaired motor function, learning, language or non-verbal communication. These include the array
of disorder, including: Autism Spectrum Disorders (ASD), Attention Deficit Hyperactivity
Disorders (ADHD) etc. There is no particular diagnosis and cure for NDDs. These disorders seem
to be result from a combination of genetic, biological, psychosocial and environmental risk factors.
Diverse scientific literature reveals the adverse effect of environmental factors specifically,
exposure of pesticides, which leads to growing number of human pathological conditions; among
these, neurodevelopmental disorder is an emerging issue nowadays.

Objective:

The current study focused on in silico identification of potential drug targets for
pesticides induced neurodevelopmental disorder including Attention Deficit Hyperactivity Disorder
(ADHD) and Autism Spectrum Disorder (ASD) and to design potential drug molecule for
the target through drug discovery approaches.

Methods:

We identified 139 candidate genes for ADHD and 206 candidate genes for ASD from
the NCBI database for detailed study. Protein-protein interaction network analysis was performed
to identify key genes/proteins in the network by using STRING 10.0 database and Cytoscape 3.3.0
software. The 3D structure of target protein was built and validated. Molecular docking was
performed against twenty seven possible phytochemicals i.e. beta amyrin, ajmaline, serpentine,
urosolic, huperzine A etc. having neuroprotective activity. The best-docked compound was
identified by the lowest Binding Energy (BE). Further, the prediction of drug-likeness and
bioactivity analysis of leads were performed by using molinspiration cheminformatics software.

Result & Conclusion:

Based on betweenness centrality and node degree as a network topological
parameter, solute carrier family 6 member 4 (SLC6A4) was identified as a common key protein in
both the networks. 3-D structure of SLC6A4 protein was designed and validated respectively.
Based on the lowest binding energy, beta amyrin (B.E = -8.54 kcal/mol) was selected as a potential
drug candidate against SLC6A4 protein. Prediction of drug-likeness and bioactivity analysis of
leads showed drug candidate as a potential inhibitor. Beta amyrin (CID: 73145) was obtained as
the most potential therapeutic inhibitor for ASD & ADHD in human.
A Survey on Computational Methods for Essential Proteins and Genes Prediction
Authors: Fang Ming , Lei Xiujuan , Guo Ling
Published: November 2018

Background:

Essential proteins play important roles in the survival or reproduction of
an organism and support the stability of the system. Essential proteins are the minimum set of
proteins absolutely required to maintain a living cell. The identification of essential proteins is a
very important topic not only for a better comprehension of the minimal requirements for cellular
life, but also for a more efficient discovery of the human disease genes and drug targets.
Traditionally, as the experimental identification of essential proteins is complex, it usually requires
great time and expense. With the cumulation of high-throughput experimental data, many
computational methods that make useful complements to experimental methods have been
proposed to identify essential proteins. In addition, the ability to rapidly and precisely identify
essential proteins is of great significance for discovering disease genes and drug design, and has
great potential for applications in basic and synthetic biology research.

Objective:

The aim of this paper is to provide a review on the identification of essential proteins
and genes focusing on the current developments of different types of computational methods, point
out some progress and limitations of existing methods, and the challenges and directions for
further research are discussed.
Development of Betamethasone Dipropionate-Loaded Nanostructured Lipid Carriers for Topical and Transdermal Delivery
Authors: Hanna Pierre A. , Ghorab Mamdouh M. , Gad Shadeed
Published: November 2018

Introduction: Betamethasone dipropionate is a highly effective corticosteroid
anti-inflammatory. However, the main drawback of its topical use is the limited skin penetration
into deeper skin layers. Also, its systemic use has shown many side effects.

Objective: The goal of this research was to formulate betamethasone dipropionate in
nanostructured lipid carriers (NLC) formulae that contain oleic acid to aid its penetration to
deeper skin layers and to aid absorption to local regions upon topical application.

Methods: NLC formulae were prepared by high shear homogenization then sonication.
Formulae were characterized for their particle size, size distribution, electric potential, occlusion
factor, entrapment efficiency, drug loading, transmission electron microscopy, in
vitro drug release, and ex vivo skin penetration. Compatibility of ingredients with drug was
tested using differential scanning calorimetry. Formulae were shown to have appropriate
characteristics. NLC formulae were superior to traditional topical formulation in drug release.

Results: Upon testing ex vivo skin penetration, betamethasone dipropionate prepared in
NLC formulae was shown to penetrate more efficiently into skin layers than when formulated
as a traditional cream. NLC formulation that contained higher percentage of oleic acid
showed higher penetration and higher amount of drug to pass through skin.

Conclusion: In general, NLC with lower oleic acid percentage was shown to deliver betamethasone
dipropionate more efficiently into deeper skin layers while that of a higher oleic
acid percentage was shown to deliver the drug more efficiently into deeper skin layers and
through the skin, transdermally.