Search

Community recovery from hazards occurs through various diffusion processes within social and spatial networks of communities. Existing knowledge regarding the diffusion of recovery in community socio-spatial networks, however, is rather limited. To bridge this gap, we created a network diffusion model to characterize the unfolding of population activity recovery in spatial networks of communities. In particular, this study aims to answer the research question "To what extent can the diffusion model capture the spatial patterns of recovery?" Using population activity recovery data derived from location-based information associated with 2017 Hurricane Harvey in the Houston area, we parameterized the threshold-based network diffusion model using the genetic algorithm and then simulated the recovery diffusion process. The results show that the spatial effects of recovery are rather heterogeneous across different areas; some spatial areas demonstrate a greater spatial effect in their recovery. Also, the results show that low-income and minority areas are community recovery multipliers; with faster recovery in these areas corresponding to accelerated recovery for the entire community. Hence, prioritizing these areas in resource allocation during recovery has the potential to accelerate could expedite the recovery of the entire community's recovery process while promoting recovery equality and equity. [ABSTRACT FROM AUTHOR]

In studying resilience in temporal human networks, relying solely on global network measures would be inadequate; latent sub-structural network mechanisms need to be examined to determine the extent of impact and recovery of these networks during perturbations, such as urban flooding. In this study, we utilize high-resolution aggregated location-based data to construct temporal human mobility networks in Houston in the context of the 2017 Hurricane Harvey. We examine motif distribution, motif persistence, temporal stability, and motif attributes to reveal latent sub-structural mechanisms related to the resilience of human mobility networks during disaster-induced perturbations. The results show that urban flood impacts persist in human mobility networks at the sub-structure level for several weeks. The impact extent and recovery duration are heterogeneous across different network types. Also, while perturbation impacts persist at the sub-structure level, global topological network properties indicate that the network has recovered. The findings highlight the importance of examining the microstructures and their dynamic processes and attributes in understanding the resilience of temporal human mobility networks (and other temporal networks). The findings can also provide disaster managers, public officials, and transportation planners with insights to better evaluate impacts and monitor recovery in affected communities. [ABSTRACT FROM AUTHOR]

In this study, the potassium adsorption for the purification of crude ammonium perrhenate solutions in the presence of various cheap and available ion exchange resins is reported for the first time. After the resin screening test, the optimum resin (Purolite® C100 resin as a strong acid cation ion exchange resin in the sodium form) was selected for morphological analysis using field emission scanning electron microscopy, which was further examined by energy-dispersive spectroscopy. Moreover, X-ray elemental mapping of the surface of C100 resin revealed homogeneous potassium adsorption. BET and TGA tests confirmed the adsorbed potassium on the C100 resin. Among the isotherm models, the Langmuir isotherm provided the best fit according to the correlation coefficients. The adsorption parameters have been scrutinized, including contact time, initial potassium concentration, temperature, and competitive binary potassium and sodium adsorption. The result of the binary system exhibited a decrease in the potassium adsorption capacity of the resin in the presence of secondary ions due to competition for adsorption sites. Kinetic characteristics of the potassium adsorption process were investigated by pseudo-first-order and pseudo-second-order, intraparticle diffusion, and Elovich models. The adsorption process has been found to match the pseudo-first-order reaction. The continuous/extended experiments and the elution test were also evaluated. [ABSTRACT FROM AUTHOR]

We present a latent characteristic in socio-spatial networks, hazard-exposure heterophily, to capture the extent to which populations with dissimilar hazard exposure could assist each other through social ties. Heterophily is the tendency of unlike individuals to form social ties. Conversely, populations in hazard-prone spatial areas with significant hazard-exposure similarity, homophily, would lack sufficient resourcefulness to aid each other to lessen the impact of hazards. In the context of the Houston metropolitan area, we use Meta's Social Connectedness data to construct a socio-spatial network in juxtaposition with flood exposure data from National Flood Hazard Layer to analyze flood hazard exposure of spatial areas. The results reveal the extent and spatial variation of hazard-exposure heterophily in the study area. Notably, the results show that lower-income areas have lower hazard-exposure heterophily possibly caused by income segregation and the tendency of affordable housing development to be located in flood zones. Less resourceful social ties in hazard-prone areas due to their high-hazard-exposure homophily may inhibit low-income areas from better coping with hazard impacts and could contribute to their slower recovery. Overall, the results underscore the significance of characterizing hazard-exposure heterophily in socio-spatial networks to reveal community vulnerability and resilience to hazards. [ABSTRACT FROM AUTHOR]

Hurricanes are one of the most catastrophic natural hazards faced by residents of the United States. Improving the public's hurricane preparedness is essential to reduce the impact and disruption of hurricanes on households. Inherent in traditional methods for quantifying and monitoring hurricane preparedness are significant lags, which hinder effective monitoring of residents' preparedness in advance of an impending hurricane. This study establishes a methodological framework to quantify the extent, timing, and spatial variation of hurricane preparedness at the census block group level using high-resolution location intelligence data. Anonymized cell phone data on visits to points-of-interest for each census block group in Harris County before 2017 Hurricane Harvey were used to examine residents' hurricane preparedness. Four categories of points-of-interest, grocery stores, gas stations, pharmacies and home improvement stores, were identified as they have close relationship with hurricane preparedness, and the daily number of visits from each CBG to these four categories of POIs were calculated during preparation period. Two metrics, extent of preparedness and proactivity, were calculated based on the daily visit percentage change compared to the baseline period. The results show that peak visits to pharmacies often occurred in the early stage of preparation, whereas the peak of visits to gas stations happened closer to hurricane landfall. The spatial and temporal patterns of visits to grocery stores and home improvement stores were quite similar. However, correlation analysis demonstrates that extent of preparedness and proactivity are independent of each other. Combined with synchronous evacuation data, CBGs in Harris County were divided into four clusters in terms of extent of preparedness and evacuation rate. The clusters with low preparedness and low evacuation rate were identified as hotspots of vulnerability for shelter-in-place households that would need urgent attention during response. Hence, the research findings provide a new data-driven approach to quantify and monitor the extent, timing, and spatial variations of hurricane preparedness. Accordingly, the study advances data-driven understanding of human protective actions during disasters. The study outcomes also provide emergency response managers and public officials with novel data-driven insights to more proactively monitor residents' disaster preparedness, making it possible to identify under-prepared areas and better allocate resources in a timely manner. [ABSTRACT FROM AUTHOR]

In a new approach, we considered the special affinity between Ni and poly-histidine tags of recombinant urate oxidase to utilize Ni-MOF for immobilizing the enzyme. In this study, a carbon paste electrode (CPE) was modified by histidine-tailed urate oxidase (H-UOX) and nickel-metal–organic framework (Ni-MOF) to construct H-UOX/Ni-MOF/CPE, which is a rapid, sensitive, and simple electrochemical biosensor for UA detection. The use of carboxy-terminal histidine-tailed urate oxidase in the construction of the electrode allows the urate oxidase enzyme to be positioned correctly in the electrode. This, in turn, enhances the efficiency of the biosensor. Characterization was carried out by X-ray diffraction (XRD), energy-dispersive X-ray spectroscopy (EDX), Fourier transform infrared spectroscopy (FTIR), Brunauer–Emmett–Teller (BET), and field emission scanning electron microscopy (FE-SEM). At optimum conditions, the biosensor provided a short response time, linear response within 0.3–10 µM and 10–140 µM for UA with a detection limit of 0.084 µM, repeatability of 3.06%, and reproducibility of 4.9%. Furthermore, the biosensor revealed acceptable stability and selectivity of UA detection in the presence of the commonly coexisted ascorbic acid, dopamine, L-cysteine, urea, and glucose. The detection potential was at 0.4 V vs. Ag/AgCl. [ABSTRACT FROM AUTHOR]

One of the new electrochemical sensors has been devised and fabricated for the highly sensitive determination of venlafaxine on the basis of ZnO nanoflowers (ZnO-NF) as modified materials. Therefore, hydrothermal methods have been used to synthesize zinc oxide nanoflowers. The formation of ZnO nanoflower has been confirmed via Fourier transform infrared (FTIR), XRD, and FESEM. Owing to the ZnO nanoflowers with the greater surface areas to oxidation of venlafaxine, venlafaxine has been sensitively determined with the linear ranges between 0.04 and 475.0 µM and LOD equal to 0.01 µM (S/N = 3). This new technique has been substantially utilized to determine venlafaxine in real samples. [ABSTRACT FROM AUTHOR]

In the present study, we utilized a novel electrochemical sensor for the determination of colchicine in 0.1 M phosphate buffer solution (pH 4.0) using differential pulse voltammetry. 1-butyl-3-methylimidazolium tetrachloroferrate ([Bmim]FeCl4) was synthesized, investigated by FT-IR, Raman and UV–Vis spectrometer and applied as magnetic ionic liquid in electrode modification. The other modifier was copper oxide nanoparticles/carbon nanofiber composite (CuO/CNF) provided by electrospinning and evaluated by scanning electron microscopy, X-ray diffraction and Fourier transform infrared spectroscopy (FT-IR). Several electro-analytical parameters such as the electrochemical behavior of the modified electrode, scan rate, type and supporting electrolyte pH were studied for the determination of colchicine. Under the optimized experimental conditions, oxidative peak current increased linearly by increasing colchicine concentration in the range of 1.0 to 100.0 nM and detection limit was obtained 0.25 nM. The relative standard deviation for six replicate analyses of 20.0 nM and 58.0 nM colchicine solution was obtained to be ± 3.17% and ± 2.08%, respectively. The proposed electrochemical sensor was successfully applied for colchicine quantification in colchicine tablet and health human plasma with satisfying results. [ABSTRACT FROM AUTHOR]

The objective of this paper is to empirically examine the impacts of infrastructure service disruptions on the well-being of vulnerable populations during disasters. There are limited studies that empirically evaluate the extent to which disruptions in infrastructure system services impact subpopulation groups differently and how these impacts relate to the wellbeing of households. Being able to systematically capture the differential experiences of sub-populations in a community due to infrastructure disruptions is necessary to highlight the differential needs and inequities that households have. In order to address this knowledge gap, this study derives an empirical relationship between sociodemographic factors of households and their subjective well-being impacts due to disruptions in various infrastructure services during and immediately after Hurricane Harvey. Statistical analysis driven by spearman-rank order correlations and fisher-z tests indicated significant disparities in well-being due to service disruptions among vulnerable population groups. The characterization of subjective well-being is used to explain to what extent infrastructure service disruptions influence different subpopulations. The results show that: (1) disruptions in transportation, solid waste, food, and water infrastructure services resulted in more significant well-being impact disparities as compared to electricity and communication services; (2) households identifying as Black and African American experienced well-being impact due to disruptions in food, transportation, and solid waste services; and (3) households were more likely to feel helpless, difficulty doing daily tasks and feeling distance from their community as a result of service disruptions. The findings present novel insights into understanding the role of infrastructure resilience in household well-being and highlights why it is so important to use approaches that consider various factors. Infrastructure resilience models tend to be monolithic. The results provide empirical and quantitative evidence of the inequalities in well-being impacts across various sub-populations. The research approach and findings enable a paradigm shift towards a more human-centric approach to infrastructure resilience. [ABSTRACT FROM AUTHOR]

Damages in critical infrastructure occur abruptly, and disruptions evolve with time dynamically. Understanding the situation of critical infrastructure disruptions is essential to effective disaster response and recovery of communities. Although the potential of social media data for situation awareness during disasters has been investigated in recent studies, the application of social sensing in detecting disruptions and analyzing evolutions of the situation about critical infrastructure is limited. To address this limitation, this study developed a graph‐based method for detecting credible situation information related to infrastructure disruptions in disasters. The proposed method was composed of data filtering, burst time‐frame detection, content similarity calculation, graph analysis, and situation evolution analysis. The application of the proposed method was demonstrated in a case study of Hurricane Harvey in 2017 in Houston. The findings highlighted the capability of the proposed method in detecting credible situational information and capturing the temporal and spatial patterns of critical infrastructure events that occurred in Harvey, including disruptive events and their adverse impacts on communities. The proposed methodology can improve the ability of community members, volunteer responders, and decision makers to detect and respond to infrastructure disruptions in disasters. [ABSTRACT FROM AUTHOR]

• The preparation of Au/reduced graphene oxide nanocomposite through a one-pot method. • The fabrication of an Au/RGO modified carbon paste elecrode. • Electrochemical determination of agnuside by differential pulse voltammetry technique. • A novel and sensitive technique with good merit figures for agnuside determination in real samples. Agnuside despite its good properties for the body, can be harmful to the kidneys in extra concentrations. So, its measurement is important. For the first time, we developed a simple, rapid and inexpensive method for the investigation of agnuside electrochemical behavior by designing a gold/reduced graphene oxide/carbon paste electrode (Au/RGO/CPE). The Au/RGO nanocomposite was synthesized through a one-pot in situ reduction of graphene oxide (GO) and HAuCl 4 in the presence of sodium citrate and the obtained product was studied by Fourier transform infrared (FT-IR), X-ray diffraction (XRD), scanning electron microscopy (SEM) and energy-dispersive X-ray spectroscopy (EDX). The anodic oxidation of agnuside has been carried out at a modified carbon paste electrode in 0.1 M phosphate buffer solution (pH 6.0) using sensitive differential pulse voltammetry (DPV). Several parameters such as the type and pH of supporting electrolyte and scan rates were optimized. This study reported a good linearity in the range of 0.050–250.0 nM and a low detection limit of 0.016 nM. The relative standard deviations (RSDs) for 10.0 nM and 100.0 nM of agnuside were obtained 3.3% and 1.2%, respectively. The sensor was successfully applied to determine agnuside in Vitex agnus castus fruit and urine sample. [ABSTRACT FROM AUTHOR]

Abstract In the present study, for the first time, we develop a sensitive voltammetric technique for the determination of pemetrexed using Pd/carbon nanofibers/methyl (trioctyl)ammonium bis(trifluoromethylsulfonyl)imide ([M3OA]+[NTF2]−) ionic liquid modified carbon paste electrode in which Nafion was utilized as binder (CPE/Pd/CNF/[M3OA]+[NTF2]−/Nafion). Composite nanofibers were synthesized by electrospinning method and characterized by SEM, TEM, XRD and FT-IR and the synthesized ionic liquid was also investigated by FT-IR and UV–Vis. Square wave voltammetry (SWV) measurements were performed to investigate the electrochemical oxidation of pemetrexed using the proposed electrode in 0.1 M phosphate buffer solution at pH 6.0. Several parameters such as pH amount, scan rate and the type of supporting electrolyte were studied for pemetrexed oxidation. In addition, selectivity, repeatability, reproducibility and stability were also evaluated. Under optimized conditions, a linear concentration was detected in the range of 1.00–35.0 nM with a detection limit of 0.33 nM by SWV. The proposed sensor was successfully applied for the quantification of pemetrexed in cancerous human plasma, pharmaceutical and health urine samples. Graphical abstract Unlabelled Image Highlights • Fabrication of Pd/carbon nanofibers by electrospinning method • Modification of carbon paste electrode by Pd/CNF/[M3OA]+[NTF2]−. • Electrochemical pemetrexed determination using SWV technique • The developed sensor being successfully applied for the determination of pemetrexed in real samples [ABSTRACT FROM AUTHOR]

Abstract For the first time, we developed an electrochemical sensor for piceatannol based on a new type of nanocomposite: graphene oxide nano sheets decorated with core-shell NiO@polypyrrole nanoparticles (NiO@Ppy/GO) mixed with nafion and casted on the surface of glassy carbon electrode. The nanocomposite was characterized by transmission electron microscopy (TEM), scanning electron microscopy (SEM), energy dispersive X-ray spectroscopy (EDX), X-ray diffraction and Fourier transform infrared spectroscopy (FT-IR) techniques. The square wave voltammetry as a sensitive technique and cyclic voltammetry were selected for the quantification of piceatannol in 0.1 M phosphate buffer solution (pH 7.0). Several parameters were evaluated such as pH value, scan rate and supporting electrolyte type for the determination of piceatannol. In addition, selectivity and repeatability measurements were also evaluated. Under the optimized conditions, linear range and limit of detection were obtained 0.01–10.0 µM and 0.003 µM, respectively. Relative standard deviation for 3.0 µM and 6.5 µM were calculated 3.25% and 1.83%, respectively. The proposed sensor was applied successfully for the quantification analysis of piceatannol in grape skin essential oil and urine sample with satisfactory results. Graphical abstract fx1 Highlights • Synthesis a NiO@Polypyrrole nanocomposite supported on graphene oxide. • Developing an electrochemical sensor by glassy carbon electrode modification. • Performing piceatannol determination in real samples using the proposed sensor. • Achieving a LOD of 0.003 µM with the prepared sensor for piceatannol determination. [ABSTRACT FROM AUTHOR]

The objective of this study is to establish a framework for analyzing infrastructure dynamics affecting the long-term steady state, and hence resilience in civil infrastructure systems. To this end, a multi-agent simulation model was created to capture important phenomena affecting the dynamics of coupled human-infrastructure systems and model the long-term performance regimes of infrastructure. The proposed framework captures the following three factors that shape the dynamics of coupled human-infrastructure systems: (i) engineered physical infrastructure; (ii) human actors; and (iii) chronic and acute stressors. A complex system approach was adopted to examine the long-term resilience of infrastructure based on the understanding of performance regimes, as well as tipping points at which shifts in the performance regime of infrastructure occur under the impact of external stressors and/or change in internal dynamics. The application of the proposed framework is demonstrated in a case of urban water distribution infrastructure using the data from a numerical case study network. The developed multi-agent simulation model was then used in examining the system resilience over a 100-year horizon under stressors such as population change and funding constraints. The results identified the effects of internal dynamics and external stressors on the resilience landscape of infrastructure systems. Furthermore, the results also showed the capability of the framework in capturing and simulating the underlying mechanisms affecting human-infrastructure dynamics, as well as long-term regime shifts and tipping point behaviors. Therefore, the integrated framework proposed in this paper enables building complex system-based theories for a more advanced understanding of civil infrastructure resilience. [ABSTRACT FROM AUTHOR]

Various studies have been increasingly performed on the reduction of sulfur content of iron ores and concentrates. The presence of sulfur in these materials causes technical problems in steel and alloys and environmental issues in the sintering of iron ore process. The achievement of higher sulfur removal rates has been an important goal since the development of sulfur removal techniques. In this research, an effort is made to separately introduce the various processes, industrial practices, and fundamental research activities to remove sulfur from iron ores, concentrates, or roasted iron ores. In this way, the optimized condition and latest innovations in sulfur removal using flotation are reviewed and the development of leaching and bioleaching techniques for sulfur reduction is introduced; following the development of thermal decomposition, physical separation methods, and magnetic separation technique are discussed. In each section, a brief introduction of fundamentals for the sulfur removal techniques and their potential advantages for sulfur removal are described and challenges for each technique are presented. Finally, the techniques are compared from technical, economic and environmental viewpoints, and future trends in desulfurization of iron ores are presented. [ABSTRACT FROM AUTHOR]

The major problems of the semiconductor nanomaterials in the photocatalytic applications for degradation of organic contaminants are fast recombination of photogenerated electron-hole pairs and low visible light harvesting. Therefore, we tried to resolve these drawbacks by coupling LaFeO 3 nanoparticles with Bi 2 WO 6 nanoflakes and constructing of binary Z-scheme heterojunction through the facile solvothermal synthesis approach. The photocatalytic activity of the LaFeO 3 /Bi 2 WO 6 heterojunction was studied through degradation of tetracycline (TC) upon visible light irradiation. The effects of experimental parameters, including LaFeO 3 /Bi 2 WO 6 dosage, initial concentration of TC, visible light irradiation time, and solution pH on the photocatalyst performance of binary nanocomposite were analyzed by response surface methodology. The results of analysis of variance confirmed that these parameters have a significant effect on the TC degradation efficiency. The value of the first-order kinetic rate constant for removal of TC using LaFeO 3 /Bi 2 WO 6 was calculated 0.1291 min−1, which was 20 and 10 times higher than pure LaFeO 3 and Bi 2 WO 6 , respectively. Besides, LaFeO 3 /Bi 2 WO 6 was shown the excellent photocatalytic stability after 4 cycles. Furthermore, the photocatalytic pathway for photodegradation of TC by binary LaFeO 3 /Bi 2 WO 6 nanocomposite was proposed according to the trapping experiments of active species and the results were signify that the h+ and . OH are the predominant reactive species for the photodegradation of TC. Overall, we believe that current novel research opens a promising route for the preparation of highly efficient LaFeO 3 /Bi 2 WO 6 photocatalyst and its usage for wastewater treatment. [ABSTRACT FROM AUTHOR]

Human mobility networks can reveal insights into resilience phenomena, such as population response to, impacts on, and recovery from crises. The majority of human mobility network resilience characterizations, however, focus mainly on macroscopic network properties; little is known about variation in measured resilience characteristics (i.e., the extent of impact and recovery duration) across macroscopic, substructure (motif), and microscopic mobility scales. To address this gap, in this study, we examine the human mobility network in eight parishes in Louisiana (USA) impacted by the 2021 Hurricane Ida. We constructed human mobility networks using location-based data and examined three sets of measures: (1) macroscopic measures, such as network density, giant component size, and modularity; (2) substructure measures, such as motif distribution; and (3) microscopic mobility measures, such as the radius of gyration and average travel distance. To determine the extent of impact and duration of recovery, for each measure, we established the baseline values and examined the fluctuation of measures during the perturbation caused by Hurricane Ida. The results reveal the variation of impact extent and recovery duration obtained from different sets of measures at different scales. Macroscopic measures, such as giant components, tend to recover more quickly than substructure and microscopic measures. In fact, microscopic measures tend to recover more slowly than measures in other scales. These findings suggest that resilience characteristics in human mobility networks are scale-variant, and thus, a single measure at a particular scale may not be representative of the perturbation impacts and recovery duration in the network as a whole. These results spotlight the need to use measures at different scales to properly characterize resilience in human mobility networks. [ABSTRACT FROM AUTHOR]

This paper presents damage assessment using a hierarchical transformer architecture (DAHiTrA), a novel deep‐learning model with hierarchical transformers to classify building damages based on satellite images in the aftermath of natural disasters. Satellite imagery provides real‐time and high‐coverage information and offers opportunities to inform large‐scale postdisaster building damage assessment, which is critical for rapid emergency response. In this work, a novel transformer‐based network is proposed for assessing building damage. This network leverages hierarchical spatial features of multiple resolutions and captures the temporal differences in the feature domain after applying a transformer encoder to the spatial features. The proposed network achieves state‐of‐the‐art performance when tested on a large‐scale disaster damage data set (xBD) for building localization and damage classification, as well as on LEVIR‐CD data set for change detection tasks. In addition, this work introduces a new high‐resolution satellite imagery data set, Ida‐BD (related to 2021 Hurricane Ida in Louisiana) for domain adaptation. Further, it demonstrates an approach of using this data set by adapting the model with limited fine‐tuning and hence applying the model to newly damaged areas with scarce data. [ABSTRACT FROM AUTHOR]

Abstract: Infrastructure systems in coastal areas are exposed to episodic flooding exacerbated by sea‐level rise stressors. To enable assessing the long‐term resilience of infrastructure to such chronic impacts of sea‐level rise, the present study created a novel complex system modeling framework that integrates: (i) stochastic simulation of sea‐level rise stressors, based on the data obtained from downscaled climate studies pertaining to future projections of sea level and precipitation; (ii) dynamic modeling of infrastructure conditions by considering regular decay of infrastructure, as well as structural damages caused by flooding; and (iii) a decision‐theoretic modeling of infrastructure management and adaptation processes based on bounded rationality and regret theories. Using the proposed framework and data collected from a road network in Miami, a multiagent computational simulation model was created to assess the long‐term cost and performance of the road network under various sea‐level rise scenarios, adaptation approaches, and network degradation effects. The results showed the capabilities of the proposed computational model for robust planning and scenario analysis to enhance the resilience of infrastructure systems to sea‐level rise impacts. [ABSTRACT FROM AUTHOR]

The aim of this research was the determination of a microRNA (miRNA) using a DNA electrochemical aptasensor. In this biosensor, the complementary complementary DNA (cDNA) of miRNA-145 (a sense RNA transcript) was the target strand and the cDNA of miRNA-145 was the probe strand. Both cDNAs can be the product of the reverse transcriptase-polymerase chain reaction of miRNA. The proposed aptasensor's function was based on the hybridization of target strands with probes immobilized on the surface of a working electrode and the subsequent intercalation of doxorubicin (DOX) molecules functioning as the electroactive indicators of any double strands that formed. Electrochemical transduction was performed by measuring the cathodic current resulting from the electrochemical reduction of the intercalated molecules at the electrode surface. In the experiment, because many DOX molecules accumulated on each target strand on the electrode surface, amplification was inherently easy, without a need for enzymatic or complicated amplification strategies. The proposed aptasensor also had the excellent ability to regenerate as a result of the melting of the DNA duplex. Moreover, the use of DNA probe strands obviated the challenges of working with an RNA probe, such as sensitivity to RNase enzyme. In addition to the linear relationship between the electrochemical signal and the concentration of the target strands that ranged from 2.0 to 80.0 nM with an LOD of 0.27 nM, the proposed biosensor was clearly capable of distinguishing between complementary (target strand) and noncomplementary sequences. The presented biosensor was successfully applied for the quantification of DNA strands corresponding to miRNA-145 in human serum samples. [ABSTRACT FROM AUTHOR]

For the first time, we coupled a microextraction technique using a magnetic ionic liquid with voltammetric determination. A hydrophobic magnetic ionic liquid that contains the tetrachloromanganate(II) anion, namely, aliquat tetrachloromanganate(II), was synthesized and used for the extraction of ascorbic acid from aqueous solutions followed by voltammetric determination. The extraction procedure was carried out using a single drop microextraction technique in which the ascorbic acid containing magnetic ionic liquid was separated with a magnet and then cast onto the surface of a carbon paste electrode modified with TiO2 nanoparticles for the voltammetric quantification of the extracted ascorbic acid. Electrochemical quantification was carried out in a blank phosphate buffer solution. After optimizing different experimental conditions, a linear concentration range of 1.50-40.0 nM with a detection limit of 0.43 nM was obtained for the determination of ascorbic acid. The presented approach was successfully applied to the determination of ascorbic acid in samples of vitamin C effervescent tablets and orange juice. [ABSTRACT FROM AUTHOR]

In the present study, poly(MImEO 8 BS)-Ni nanocomposite was synthesized and applied to modify a glassy carbon electrode along with polymeric ionic liquids (PILs). The electrochemical investigation of the modified electrode as well as its efficiency for voltammetric oxidation of risperidone is explained. The electrode was used to study the voltammetric oxidation of risperidone employing cyclic voltammetry (CV), linear sweep voltammetry (LSV), chronoamperometry and square-wave voltammetry (SWV) as diagnostic techniques. It has been observed that the oxidation of risperidone at the surface of modified electrode occurs at a potential of about 130 mV less positive than that of an unmodified glassy carbon electrode. SWV showed a linear dynamic range from 5.0 × 10 − 7 to 8.0 × 10 − 5 M and a detection limit of 7.3 × 10 − 8 M for risperidone. Moreover, this modified electrode was utilized for simultaneous determination of risperidone and methylphenidate. Finally, the modified electrode was employed for determination of risperidone and methylphenidate in pharmaceutical compounds. [ABSTRACT FROM AUTHOR]

In the current study, poly(MImEO8BS)-Ni nanocomposite was synthesized and applied to modify a glassy carbon electrode along with conductive polymeric ionic liquids. The electrochemical investigation of the modified electrode as well as its efficiency for voltammetric oxidation of warfarin is elucidated. The electrode was used to study the voltammetric oxidation of warfarin by employing cyclic voltammetry (CV), linear sweep voltammetry (LSV), chronoamperometry, and square wave voltammetry (SWV) as diagnostic techniques. It has been observed that warfarin oxidation at the surface of modified electrode occurs at a potential of about 230 mV which is less positive than that of an unmodified glassy carbon electrode. SWV demonstrated a linear dynamic range from 1.0×10 −6 to 1.0×10 −4 M and a detection limit of 1.5×10 −7 M for warfarin. In addition, this modified electrode was utilized for simultaneous determination of warfarin and tramadol. Finally, the modified electrode was employed for determination of warfarin and tramadol in pharmaceutical compounds. [ABSTRACT FROM AUTHOR]

The authors present a voltammetric immunoassay for the quantification of the prostate specific antigen (PSA), a well-established tumor marker. Biotinylated anti- PSA antibodies were immobilized on the surface of a nano-TiO2-modified carbon paste electrode using specific interaction between streptavidin and biotin. Streptavidin itself was covalently grafted to the electrode surface via 4-aminobenzoic acid film. Signal transduction was then performed using polyclonal antibodies conjugated with horseradish peroxidase (HRP) and thionine. An amplified catalytic reduction current was observed in the presence of HO because more than one polyclonal antibody linked to each antigen. Each step of the preparation of the immunosensor was monitored via electrochemical impedance spectroscopy. The electrode, if operated at a typical potential of 0.3 V vs. Ag/AgCl and using hexacyanoferrate as an electrochemical probe, exhibits linear responses in the 0.10 to 5.0 ng·mL and 5.0 to 100 ng·mL PSA concentration ranges, with a detection limit of 200 pg·mL. The accuracy of the biosensor was confirmed by analyzing a certified human serum sample, and this indicated that the immunosensor is well suited for the quantification of PSA. [ABSTRACT FROM AUTHOR]

A novel conductive polymeric ionic liquid (IL)-Fe3O4 nanocomposite (represented as PIL-Fe3O4) based on inorganic-organic hybrid material was synthesized using two different methods. Nuclear magnetic resonance, Fourier transform infrared, X-ray diffraction, and field emission scanning electron microscopy characterized the structures of IL, Fe3O4 nanoparticles, and PIL-Fe3O4. The electrochemical sensors based on PIL-Fe3O4-modified glassy carbon electrode were fabricated, and each of these nanocomposites was examined for the ability to determine amlodipine besylate (AMD). The electrochemical study of the modified electrodes, as well as its efficiency for the electro-oxidation of AMD, was described in 0.1 M phosphate-buffered solution (pH 7.0) using voltammetric methods. The results exhibit a linear dynamic range from 1 to 500 nM and a detection limit of 0.36 nM. Finally, the modified electrode was used for the determination of AMD in pharmaceutical and biological samples. [ABSTRACT FROM AUTHOR]

Vulcan XC-72R carbon supported Pd and Pd–Mo alloys of different Pd:Mo atomic ratios were prepared by hydrothermal synthesis method. The bimetallic nanoalloys were characterized by powder X-ray diffractometry and inductively coupled plasma-atomic emission spectroscopy to determine their crystal structures and elemental compositions. Alloy formation of the nanocatalysts was proven by energy dispersive X-ray spectroscopy line profiles using field emission scanning electron microscopy. The performance of as-prepared nanocatalysts was evaluated for the reactions of methanol, ethanol, ethylene glycol and glycerol electrooxidation in alkaline media by cyclic voltammetry, linear sweep voltammetry and chronoamperometric measurements. It was found that bimetallic Pd–Mo/VC catalysts have higher activity due to different electronic structure as compared to the monometallic palladium. Also, the Pd 3 Mo/VC catalyst showed excellent catalytic activity, high durability and stability which indeed propose it to be as a promising electrocatalyst for future direct alcohol fuel cells. [ABSTRACT FROM AUTHOR]

The objective of this study is to create and test an integrated framework for assessment of vulnerability to uncertainty in complex projects. In the proposed framework, construction projects are conceptualized as metanetworks composed of different nodes (i.e., human agents, information, resources, and tasks) and links. The effects of uncertain events are translated into perturbations in the nodes and links of project metanetworks. These uncertainty-induced perturbations are reflected as transformations in a project's topological structure, and thus negatively affect the efficiency of the project's metanetwork. The extent of the variation in the efficiency of a project's metanetwork is used to determine the extent of vulnerability to uncertainty. The application of the proposed framework is shown in an illustrative case study related to a tunneling project. In the case study, various scenarios related to different uncertain events were simulated through the use of dynamic network analysis and Monte Carlo simulation. The illustrative case study demonstrated the application of the proposed framework for predictive assessment and proactive mitigation of vulnerability to uncertainty based on evaluation of dynamic interactions between various entities and networks in construction projects. The proposed framework integrates elements from complex systems, dynamic network analysis, and Monte Carlo simulation approaches, and it provides a novel computational framework for ex-ante evaluation of vulnerability to uncertainty in civil engineering projects. [ABSTRACT FROM AUTHOR]

A simple and novel ferrocene-nanofiber carbon paste electrode was developed to determine curcumin in a phosphate buffer solution at pH = 8. ZnO nanoparticles were produced via a sonochemical process and composite nanofibers of PVP/ZnO were prepared by electrospinning. The characterization was performed by SEM, XRD and IR. The results suggest that the electrospun composite nanofibers having a large surface area promote electron transfer for the oxidation of curcumin and hence the FCNFCPE exhibits high electrocatalytic activity and performs well in regard to the oxidation of curcumin. The proposed method was successfully applied for measurement of curcumin in urine and turmeric as real samples. [ABSTRACT FROM AUTHOR]

In the present work a sensitive and selective electrochemical sensor was fabricated based on a glassy carbon electrode which has been modified with Pd nanoparticles loaded on Vulcan carbon/conductive polymeric ionic liquid composite nanofibers. The nanostructures were characterized by UV–Vis, FT-IR, FESEM, EDX and XRD techniques. The electrochemical study of the modified electrode, as well as its efficiency for the electrooxidation of tramadol was described in 0.1 M phosphate buffered solution (PBS) (pH 7.0) using cyclic voltammetry, linear sweep voltammetry, chronoamperometry and square wave voltammetry as diagnostic techniques. It has been found that application of the composite nanofibers result in a sensitivity enhancement and a considerable decrease in the anodic overpotential, leading to negative shifts about 200 mV in peak potential. The results exhibit a linear dynamic range from 0.05 μM to 200 μM and a detection limit of 0.015 μM for tramadol. Finally, the modified electrode was used for the determination of tramadol in pharmaceutical and biological samples. [ABSTRACT FROM AUTHOR]

The ASCE Body of Knowledge and the ABET Engineering Accreditation Commission have emphasized a broad set of competencies required by 21st century civil engineers. In addition to competencies that are traditionally technical, these organizations recognize that professional competencies such as leadership, the ability to design sustainable systems, effective communication, and interdisciplinary teamwork are among the many skills required by engineers of the future. To develop and enhance all of these proficiencies within the undergraduate curriculum, there is a need to take an approach that interconnects all of these outcomes throughout the curriculum, or a "networked" approach. This paper discusses service learning as a potential approach for facilitating the broad set of foundational, technical, and professional learning outcomes cited by ASCE and ABET, by investigating two case studies within the Engineering Projects in Community Service program at Purdue University. The case studies are two service-learning projects from one large, multidisciplinary, vertically integrated student design team. One project focuses on sustainable and energy efficient housing for Habitat for Humanity (HFH) in Indiana, whereas the other project focuses on affordable houses for HFH in Haiti. The current analysis of these cases suggest that service-learning projects can provide a unique learning experience for the students to develop and synthesize the broad set of foundational, technical, and professional skills by integrating learning outcomes [ABSTRACT FROM AUTHOR]

There is an urgent need for policies to close the existing financing gap for civil infrastructure. However, identification of the desired scenarios for the closure of the financing gap is complex because there are many factors that affect investment in infrastructure. Thus, comprehensive models are required to (1) simulate the impacts of policies, and (2) identify the highly likely scenarios for desired policy outcomes. The objective of this paper is to create a simulation model for ex-ante analysis of financing policies in highway transportation infrastructure in the United States. Using the agent-based technique, this model simulates the microbehaviors of state Departments of Transportation, private institutional investors, and the public. Using the output of the simulation model, financing landscapes of the U.S. transportation infrastructure are developed. The simulated landscape is shown to be helpful in identifying the highly likely scenarios leading to a high level of investment in highway transportation infrastructure under the existing infrastructure investment structures and budget constraints in the United States. The study presented in this paper is novel with respect to (1) the application of the system-of-systems modeling in the analysis of transportation infrastructure financing policies, (2) identification of the desired policy scenarios and their likelihoods for closure of the financing gap in the presence of uncertainties and adaptive behaviors, and (3) simulation and visualization of the impacts of financing policies at the state and national levels. The model promotes a data-driven policy analysis and provides policymakers with a tool to simultaneously account for the impacts of several factors and uncertainties. [ABSTRACT FROM AUTHOR]

Deviation from the traction path affects the operation of composting machines that work in an offset manner and reduces their performance. In this article, a compost mixing machine behind a tractor, which deviates from the movement path during operation, was investigated and evaluated. The equations governing the performance of the extraction machine and the effective parameters in the optimal performance of the device were determined and their effect on the deviation of the device was investigated. The results of this research show that by changing the parameters of the machine without increasing its weight in order to reduce the deviation from the movement path, it is possible to significantly increase the balance of the machine and work efficiency and reduce the deviation from the movement path. In this investigation, it was found that by changing several parameters such as the longitudinal and transverse distance of the composting machine, the friction coefficient, etc., the deviation angle of the machine decreases from 17 degrees to less than 4 degrees. Based on the theory presented in this article, the device was designed, built and used in Gulab Zahra Kerman Company, and its performance is satisfactory, and the practical review of each of the parameters presented in this article will be presented in other articles. [ABSTRACT FROM AUTHOR]

Flood nowcasting refers to near-future prediction of flood status as an extreme weather event unfolds to enhance situational awareness. The objective of this study was to adopt and test a novel structured deep-learning model for urban flood nowcasting by integrating physics-based and human-sensed features. We present a new computational modeling framework including an attention-based spatial–temporal graph convolution network (ASTGCN) model and different streams of data that are collected in real-time, preprocessed, and fed into the model to consider spatial and temporal information and dependencies that improve flood nowcasting. The novelty of the computational modeling framework is threefold: first, the model is capable of considering spatial and temporal dependencies in inundation propagation thanks to the spatial and temporal graph convolutional modules; second, it enables capturing the influence of heterogeneous temporal data streams that can signal flooding status, including physics-based features (e.g., rainfall intensity and water elevation) and human-sensed data (e.g., residents' flood reports and fluctuations of human activity) on flood nowcasting. Third, its attention mechanism enables the model to direct its focus to the most influential features that vary dynamically and influence the flood nowcasting. We show the application of the modeling framework in the context of Harris County, Texas, as the study area and 2017 Hurricane Harvey as the flood event. Three categories of features are used for nowcasting the extent of flood inundation in different census tracts: (i) static features that capture spatial characteristics of various locations and influence their flood status similarity, (ii) physics-based dynamic features that capture changes in hydrodynamic variables, and (iii) heterogeneous human-sensed dynamic features that capture various aspects of residents' activities that can provide information regarding flood status. Results indicate that the ASTGCN model provides superior performance for nowcasting of urban flood inundation at the census-tract level, with precision 0.808 and recall 0.891, which shows the model performs better compared with other state-of-the-art models. Moreover, ASTGCN model performance improves when heterogeneous dynamic features are added into the model that solely relies on physics-based features, which demonstrates the promise of using heterogenous human-sensed data for flood nowcasting. Given the results of the comparisons of the models, the proposed modeling framework has the potential to be more investigated when more data of historical events are available in order to develop a predictive tool to provide community responders with an enhanced prediction of the flood inundation during urban flood. [ABSTRACT FROM AUTHOR]

A novel carbon paste electrode modified with ZnO nanorods and 3-(4′-amino-3′-hydroxy-biphenyl-4-yl)-acrylic acid (3,4′AAZCPE) was fabricated. The electrochemical study of the modified electrode, as well as its efficiency for electrocatalytic oxidation of dopamine, is described. It has been found that the oxidation of dopamine at the surface of modified electrode occurs at a potential of about 180 mV less positive than that of an unmodified carbon paste electrode. The detection limit of 5.6 × 10 −8 M for dopamine was obtained using square wave voltammetry (SWV). In addition, this modified electrode was used for simultaneous determination of dopamine, melatonin, methionine and caffeine. Finally, the modified electrode was used for determination of dopamine, melatonin, methionine and caffeine in human blood serum and urine samples. [ABSTRACT FROM AUTHOR]

Oleuropein (Ole), naturally occurring phenolic compound found in olive products, is well known for its benefits for human health. In the present work, a simple, sensitive and rapid determination of Ole was achieved using a label-free electrochemical DNA biosensor. The application was related to the molecular interaction between Ole and double-stranded DNA (dsDNA). So, the voltammetric behavior of Ole at the surface of a DNA-immobilized chitosan-modified carbon paste electrode was studied using differential pulse voltammetry (DPV) where the oxidation peak current of Ole was measured as an analytical signal. A considerable increase was observed in the oxidation signal of Ole at the DNA-coated electrode compared with the DNA-free electrode, indicating the pre-concentration of Ole due to the interaction with the surface-confined DNA layer. In order to use the proposed sensor for real samples, different parameters affecting Ole signal such as, immobilization time and potential, accumulation time and pH, and stripping pH were optimized. Under optimized experimental conditions, a linear concentration range of 0.30–12 μmol L − 1 with a detection limit of 0.090 μmol L − 1 was obtained for Ole determination. The proposed biosensor was successfully applied to the determination of Ole in olive leaf extract and human serum samples. [ABSTRACT FROM AUTHOR]

While traditional financing approaches such as federal and state grants funded by taxation are insufficient to address the existing need, innovative financing such as novel public private partnership models, credit enhancement tools, and new bonding instruments has emerged to expand the fiscal space of public agencies for infrastructure development. Formulating innovative financing approaches is one of the challenges faced by policymakers to address the ever growing need for restoring the failing civil infrastructure in the U.S. Public support/opposition is one of the major drivers/disruptors of innovative financing. Assessment of public perceptions is a major component towards gaining public support and developing sustainable infrastructure financing policies. The objective of this study is to investigate the determinants of public perceptions of innovative financing. Data obtained from public survey of 616 individuals from 50 states in the U.S. is analyzed to investigate the effects of: (a) economic factors, (b) infrastructure conditions, and (c) personal characteristics of the public on the knowledge, awareness, perceptions, and attitudes of the public towards innovative financing. The findings reveal that the likelihood of public support of innovative financing is insensitive to economic conditions and is affected by the factors related to infrastructure condition such as the level of need for infrastructure renewal, the ability to protect the public against natural disasters, and the history of using innovative financing for infrastructure renewal. The findings also show that 57% of the sample population in the U.S. were not knowledgeable about different methods for financing infrastructure projects and 77% of the sample population in the U.S. were not aware of the activities of public organizations for finding innovative financing solutions for infrastructure projects. Based on the findings, two main strategies have been proposed for infrastructure agencies to enhance their efforts towards gaining public acceptance of innovative financing: (i) enhance strategies to facilitate learning for the public about innovative financing in infrastructure projects and (ii) improve marketing and citizen involvement strategies to get the public to buy-in to innovative financing methods. The findings can enhance the current efforts of public agencies related to educating the public and citizen involvement strategies by incorporating public preferences in policy development to enhance the likelihood of public support of innovative financing methods. Potential improvements can be made in changing the key messages in educating the public, using more effective strategies for communicating complicated financing concepts, and highlighting the success stories and benefits of innovative financing in other states and countries. [ABSTRACT FROM AUTHOR]

Olanzapine is the frequently prescribed drug in children and adolescents with bipolar disorder, but unfortunately it has metabolic side-effects. On the other hand, in a number of melatonin studies on sleep cycle, regulation of metabolic abnormalities has been reported. Therefore, we aimed to study effects of melatonin in reducing metabolic side-effects of olanzapine in 11-17 year-old patients with bipolar disorder. Seventy-seven 11-17 year-old outpatients entered into the study after their initial diagnosis of bipolar mood disorder by a psychiatrist. After assessing inclusion and exclusion criteria, 48 patients consented to participate in the study. Of this number, 24 patients were allocated to olanzapine, lithium carbonate, and melatonin and 24 patients were allocated to olanzapine, lithium carbonate, and placebo. Young mania rating scale was performed at baseline. Before treatment initiation and at sixth and twelfth weeks after treatment, Lipid profile, Fasting Blood Sugar (FBS), Systolic Blood Pressure (SBP) and Diastolic Blood Pressure (DBP) were measured. ANOVA with repeated measure and independent sample t-test were used for data analysis. Nineteen patients in each group completed the study and yielded data for analysis. ANOVA with repeated measure showed that FBS and Triglyceride (TG) (especially in boys) demonstrated greater increase in the placebo group compared to the melatonin group but the differences were not statistically significant. Melatonin significantly inhibited the rise in Total Cholesterol levels compared to placebo (P=0.032). Mean SBP rose more slowly in the melatonin group (1.05mmHg) compared to placebo (6.36 mmHg) (P=0.023). The trends in DBP did not show any significant pattern. Administration of melatonin along with olanzapine and lithium carbonate could significantly inhibit the rise in cholesterol level and SBP compared to placebo. The effect of melatonin on TG was more obvious in boys. Melatonin was more effective in prevention of SBP rise. [ABSTRACT FROM AUTHOR]

A carbon paste electrode was modified with ZnO nanorods and 3-(4′-amino-3′-hydroxy-biphenyl-4-yl)-acrylic acid (3,4′AAZCPE) to cause electrocatalysis of norepinephrine oxidation. It has been found that the oxidation of norepinephrine at the surface of modified electrode occurs at a potential of about 180 mV less positive than that of an unmodified carbon paste electrode. Square wave voltammetry (SWV) exhibits linear dynamic range from 1.0×10−7 to 8.0×10−5 M and a detection limit of 3.9×10−8 M for norepinephrine. In addition, this modified electrode was used for simultaneous determination of norepinephrine, tyrosine and nicotine. [ABSTRACT FROM AUTHOR]

A novel carbon paste electrode modified with ZnO nanorods and 5-(4′-amino-3′-hydroxy-biphenyl-4-yl)-acrylic acid (3,4′-AAZCPE) was fabricated. The electrochemical study of the modified electrode, as well as its efficiency for the electrocatalytic oxidation of levodopa, is described. The electrode was employed to study the electrocatalytic oxidation of levodopa, using cyclic voltammetry (CV), chronoamperometry (CHA), and square-wave voltammetry (SWV) as diagnostic techniques. It has been found that the oxidation of levodopa at the surface of the modified electrode occurs at a potential of about 370 mV less positive than that of an unmodified carbon paste electrode. The SWV results exhibit a linear dynamic range from 1.0 × 10−7 M to 7.0 × 10−5 M and a detection limit of 3.5 × 10−8 M for levodopa. In addition, this modified electrode was used for the simultaneous determination of levodopa and carbidopa. Finally, the modified electrode was used for the determination of levodopa and carbidopa in some real samples. [ABSTRACT FROM AUTHOR]

According to the National Academy of Engineering, innovations such as intelligent transportation systems, alternative fuels, and smart grids are critical to enhancing the resilience and sustainability of infrastructure systems. One key to realizing infrastructure innovations is effective policymaking based on a comprehensive analysis of the system. However, policy analysis in infrastructure systems is difficult because of the existence of complex adaptive behaviors and uncertainties. The objective of this paper is to create an ex-ante analysis framework using Agent-Based simulation to facilitate incorporation of uncertainties and complex adaptive behaviors of stakeholders in the analysis of infrastructure policies. The proposed framework includes three phases: definition, abstraction, and implementation. First, the steps in each phase will be discussed. Then, the application of the framework is demonstrated for the assessment of financial innovation policies for U.S. transportation infrastructure. Using hybrid agent-based/system dynamics techniques, a computational model is created to simulate the micro behaviors of state departments of transportation, private institutional investors, and the public. The results of the model include the visualization of the outcomes of different policies and the identification of the desired policy landscapes. The proposed framework provides policymakers with an integrated methodology through which an infrastructure policy problem is formulated, micro behaviors of the agents are modeled, the policy landscape is created, and the desired scenarios are identified. [ABSTRACT FROM AUTHOR]

A simple and sensitive label-free electrochemical DNA biosensor was proposed for the rapid determination of uric acid (UA) using a carbon nano tube paste electrode (CNTPE) modified with salmon sperm dsDNA. At first, the interaction between UA and the DNA was studied using differential pulse voltammetry (DPV). The addition of the DNA to UA solution resulted in a decrease in the peak current of UA and at the same time, a positive shift in the peak potential indicating an intercalative interaction. Then, the voltammetric response of a DNA-immobilized CNTPE was investigated for the determination of UA. The immobilization of the DNA was carried out using acid-functionalized carbon nanotubes and studied using Fe(CN)6 3−/Fe(CN)6 4− redox indicator. Compared with unmodified CNTPE, the oxidation signal of UA showed a significant increase at the DNA-coated electrode, and shifted to more positive potentials attributed to the pre-concentration of UA at the electrode surface due to interaction with the surface-confined DNA layer. This interaction was used for the fabrication of a simple and sensitive biosensor for determining UA. After the optimization of operational parameters, a linear dependence of the peak current on the UA concentration was observed in the range of 7.0×10−7 to 1.1×10−4 molL−1, with the detection and quantification limits of 1.8×10−7 and 5.8×10−7 molL−1, respectively. The proposed biosensor was successfully applied to validate its capability for the analysis of UA in human serum and urine samples. [ABSTRACT FROM AUTHOR]

In this study, a carbon paste electrode modified with TiO2 nanoparticles and ferrocene monocarboxylic acid (FM) was used to prepare a novel electrochemical sensor. The objective of this novel electrode modification was to seek new electrochemical performances for the detection of methyldopa in the presence of folic acid and glycine. The peak potentials recorded in a phosphate buffer solution (PBS) of pH7.0 were 325, 750 and 880mV vs. Ag/AgCl/KCl (3.0M) for methyldopa, folic acid and glycine, respectively. Under the optimum pH of 7.0, the oxidation of methyldopa occurred at a potential about 160mV less positive than that of the unmodified carbon paste electrode (CPE). The response of catalytic current with methyldopa concentration showed a linear relation in the range from 2.0×10−7 to 1.0×10−4 M with a detection limit of 8.0 (±0.2)×10−8 M. [ABSTRACT FROM AUTHOR]

In the last decade, the state departments of transportation in the US have experienced an increase in their construction projects, while the level of their in-house inspection staff and resources has either remained the same or declined. Previous studies have found that one strategy that may reduce the inspection workload is prioritizing construction activities for inspection. However, reducing the number of inspections also has its risks, such as functional failures and reduced design life. Thus, available inspection resources should be allocated to the activities with significant risk consequences if inspection is reduced. The objective of this paper is to develop a risk-based inspection protocol to facilitate efficient allocation of available inspection resources to minimize the risks associated with reduced inspection. First, the risk consequences associated with reduced inspection are identified for various construction activities linked to transportation projects. Based on data collected from 23 state departments of transportation, 58 engineers and inspectors from the Indiana Department of Transportation and 20 inspection consultants in the Midwest, the subjective perceived probabilities associated with the occurrence of each risk consequence are encoded by using fuzzy analysis, from which the risk impacts due to reduced inspection are obtained. The construction activities are prioritized based on the risk impacts associated with reduced inspection into five priority levels. The greater the risk impacts are as a result of reduced inspection, the higher the priority would be for inspection of that activity. Thus, the proposed protocol can be used for resource allocation based on risk impacts. The proposed list of prioritized construction activities can assist project and program managers in state departments of transportation in better allocating their limited inspection resources while reducing the risks due to reduced inspection. [ABSTRACT FROM AUTHOR]

Performing highway construction operations during nighttime hours has emerged as a response to traffic congestions caused by daytime lane closures. Work zone conditions at night may be different from those during the day, and nighttime factors that affect project metrics (i.e., safety, quality, and productivity) should be carefully considered during the planning of nighttime projects. Currently, there is no methodology for quantifying the effects of nighttime factors on the productivity of construction operations. The objective of this study therefore is to create such a methodology, specifically for asphalt paving projects, focusing on visibility, personnel fatigue, and glare. The methodology is demonstrated using an example case. First, nighttime qualitative (subjective) factors affecting the productivity of asphalt paving operations are identified. A productivity index (PI) is then estimated to account for these factors. The PI value is subsequently used to modify the baseline productivity simulated by a discrete event model of a paving operation, and is then compared with the actual productivity of the case study project. The analysis indicates that the productivity of the asphalt paving operation in the case study can be predicted within an acceptable accuracy range, implying that the calculated nighttime PI can adequately capture the effects of nighttime factors. Quantification of the effects of nighttime factors could help practitioners understand the extent of these effects on their projects. Because nighttime operations are usually more expensive-attributable to overtime payments, night premium payments, lighting expenses, and costs associated with enhanced traffic control-a better estimate of productivity during the early stages of the project, and accounting for the effects of nighttime factors, could lead to better planning and result in cost savings. [ABSTRACT FROM AUTHOR]

Adsorption process is an effective and promising procedure for the removal of contaminations from wastewater. Nanocomposites have attracted extensive attention in the adsorption field owning to large surface/volumes ratio and large number of active sites. We aim at fabricating a novel binary g‐C3N4/ZnV2O4 nanocomposite, which can be used for removal of crystal violet dye from aqueous solution via the adsorption process. The as‐synthesized nanocomposite was well characterized by X‐ray diffraction (XRD), Fourier‐transform infrared spectroscopy (FTIR), field emission scanning microscope (FESEM), energy‐dispersive X‐ray (EDX), and mapping analyses. The effects of four key experimental parameters on the adsorption process, including adsorbent dosage, initial concentration of crystal violet dye, adsorption time, and solution pH, were investigated by using central composite design‐based response surface methodology. The high adsorption efficiency of 99.67% was obtained at the adsorbent dosage of 19.776 mg, initial crystal violet concentration of 20.048 ppm, contact time of 59.20 min, and pH of 8. The correlation coefficients values (R2 of 0.9969, predicted‐R2 of 0.9910, and adjusted‐R2 of 0.9948), model p value = 0.0001, and model F value = 489.78 confirm the adequacy and predictability of the proposed model. The results of adsorption kinetics demonstrate that the adsorption of crystal violet by g‐C3N4/ZnV2O4 was performed by chemical adsorption. Also, the Langmuir model was fitted effectively with the adsorption data. Furthermore, the mechanism of adsorption was explained via π–π stacking interaction, n–π stacking interaction, electrostatic attraction, coordination bonding, and hydrogen bonding. [ABSTRACT FROM AUTHOR]

Infrastructure service disruptions impact households in an affected community disproportionally. To enable integrating social equity considerations in infrastructure resilience assessments, this study created a new computational multi‐agent simulation model, which enables integrated assessment of hazard, infrastructure system, and household elements and their interactions. With a focus on hurricane‐induced power outages, the model consists of three elements: (1) the hazard component simulates exposure of the community to a hurricane with varying intensity levels; (2) the physical infrastructure component simulates the power network and its probabilistic failures and restoration under different hazard scenarios; and (3) the households component captures the dynamic processes related to preparation, information‐seeking, and response actions of households facing hurricane‐induced power outages. We used empirical data from household surveys from three hurricanes (Harvey, Florence, and Michael) in conjunction with theoretical decision‐making models to abstract and simulate the underlying mechanisms affecting the experienced hardship of households when facing power outages. The multi‐agent simulation model was then tested in the context of Harris County, Texas, and verified and validated using empirical results from Hurricane Harvey in 2017. Then, the model was used to examine the effects of different factors—such as forewarning durations, social network types, and restoration and resource allocation strategies—on reducing the societal impacts of service disruptions in an equitable manner. The results show that improving the restoration prioritization strategy to focus on vulnerable populations is an effective approach, especially during high‐intensity events, to enhance equitable resilience. The results show the capability of the proposed computational model for capturing the dynamic and complex interactions in the nexus of households, hazards, and infrastructure systems to better integrate human‐centric aspects in resilience planning and assessment of infrastructure systems in disasters. Hence, the proposed model and its results could provide a new tool for infrastructure managers and operators, as well as for disaster managers, in devising hazard mitigation and response strategies to reduce the societal impacts of power outages in an equitable manner. [ABSTRACT FROM AUTHOR]

Abstract: In this article, we consider ionic liquid based ultrasound-assisted dispersive liquid–liquid microextraction of trace amounts of rhodium from aqueous samples and show that this is a fast and reliable sample pre-treatment for the determination of rhodium ions by flame atomic absorption spectrometry. The Rh(III) was transferred into its complex with 2-(5-bromo-2-pyridylazo)-5-diethylamino phenol as a chelating agent, and an ultrasonic bath with the ionic liquid, 1-octyl-3-methylimidazolium bis (trifluoromethylsulfonyl) imide at room temperature was used to extract the analyte. The centrifuged rhodium complex was then enriched in the form of ionic liquid droplets and prior to its analysis by flame atomic absorption spectrometry, 300μL ethanol was added to the ionic liquid-rich phase. Finally, the influence of various parameters on the recovery of Rh(III) was optimized. Under optimum conditions, the calibration graph was linear in the range of 4.0–500.0ngmL−1, the detection limit was 0.37ngmL−1 (3S b/m, n =7) and the relative standard deviation was ±1.63% (n =7, C =200ngmL−1). The results show that ionic liquid based ultrasound assisted dispersive liquid–liquid microextraction, combined with flame atomic absorption spectrometry, is a rapid, simple, sensitive and efficient analytical method for the separation and determination of trace amounts of Rh(III) ions with minimum organic solvent consumption. [ABSTRACT FROM AUTHOR]

n organo-nanoclay is used as a new, easily accessible, and stable solid sorbent for the preconcentration of trace amounts of rhodium ions from aqueous solution, this followed by its determination by flame atomic absorption spectrometry (FAAS). Rh(III) ion was first complexed with 2,3,5,6-tetra(2-pyridyl) pyrazine (TPPZ) at pH values between 3.0 and 4.7, and then the complex was then adsorbed onto the nanoclay. The rhodium ions were eluted from the sorbent with HCl. The rhodium in the effluent was determined by FAAS. The linear analytical range is between 0.14 ng mL and 20.0 μg mL in the initial solution, the relative standard deviation at 2.0 μg mL of rhodium is 2.6% ( n = 8), the detection limit is 0.03 ng mL, and the preconcentration factor is 140. Experimental parameters including the pH, eluent type, interference by other ions and breakthrough volume were optimized. The method was applied to the determination of rhodium in water, road dust and synthetic samples. [ABSTRACT FROM AUTHOR]

Abstract: In this work, the applicability of modified organo nanoclay as a new and easy prepared solid sorbent for the preconcentration of trace amounts of Au(III) ion from water samples is studied. The organo nanoclay was modified with 5-(4′-dimethylamino benzyliden)-rhodanine and used as a sorbent for separation of Au(III) ions. The sorption of gold ions was quantitative in the pH range of 2.0–6.0. Quantitative desorption occurred with 6.0mL of 1.0molL−1 Na2S2O3. The amount of eluted Au(III) was measured using flame atomic absorption spectrometry. In the initial solution the linear dynamic range was in the range of 0.45ngmL−1 to 10.0μgmL−1, the detection limit was 0.1ngmL−1 and the preconcentration factor was 105. Also, the relative standard deviation was ±2.3% (n =8 and C =2.0μgmL−1) and the maximum capacity of the sorbent was 3.9mg of Au(III) per gram of modified organo nanoclay. The influences of the experimental parameters including sample pH, eluent volume and eluent type, sample volume, and interference of some ions on the recoveries of the gold ion were investigated. The proposed method was applied for preconcentration and determination of gold in different samples. [Copyright &y& Elsevier]

The selection of an appropriate project delivery system that suits all project and owner needs is one of the key decisions to a successful project. Therefore, this decision should be made based on thorough analysis. In this paper, a fuzzy multiattribute decision-making (FMADM) model is developed. The model accounts for uncertainties and imprecision in the decision space as well as fuzziness in the nature of the decision attributes. The model utilizes fuzzy decision-making approach in order to evaluate the membership function corresponding to the utility of each project delivery alternative. Project delivery system alternatives are ranked using fuzzy technique for order preference by similarity to ideal solution (TOPSIS) method based on their utility membership functions and by evaluating the distance of each project delivery alternative from fuzzy ideal solutions. In the TOPSIS method, alternatives are ranked based on their closeness coefficient (CC). In addition, the risk attitude of the decision maker is considered in the model by using derived utility membership functions corresponding to the risk attitude of the decision maker. The model is applied to a petrochemical project as a case study. In the case study, the model outcome that ranked Turnkey system as the best system conforms to the lessons learned by the decision maker from several past projects. Moreover, sensitivity analysis is done in the case study. The results show the significant value of the FMADM model for selecting appropriate project delivery system for projects. [ABSTRACT FROM AUTHOR]