Bottom-up Methodology Research Articles

Nano-antibiotic based on silver nanoparticles functionalized to the vancomycin-cysteamine complex for treating Staphylococcus aureus and Enterococcus faecalis.

Bacterial resistance is defined as a microorganism's capacity to develop mechanisms for resisting a determined antimicrobial. Gram-positive bacteria, such as Staphylococcus aureus (S. aureus) and Enterococcus faecalis (E. faecalis), are internationally recognized among the isolates with this resistance profile. In this context, the demand for new medicines has risen, and silver nanoparticles (AgNPs) have been highlighted, especially for their anti-bacterial effects. To develop a nano-antibiotic for treating these Gram-positive strains, we herein report synthesizing and characterizing a nano-antibiotic based on AgNPs functionalized with the complex vancomycin-cysteamine. AgNPs were produced using the bottom-up methodology and functionalized with vancomycin modified by the carbodiimide chemistry, forming Ag@vancomycin. Susceptibility tests were performed using S. aureus and E. faecalis strains to assess the bacteriostatic and bactericidal potential of the developed nano-antibiotic. Fourier transform infrared spectroscopy measurements showed the efficacy of vancomycin chemical modification, and the characteristic bands of AgNPs functionalization with the antibiotic. The increase in the nano-antibiotic average hydrodynamic diameter observed by dynamic light scattering proved the presence of vancomycin at the surface of AgNPs. The data from the minimum inhibitory concentration and minimal bactericidal concentration assays tested on standard and clinical planktonic strains of S. aureus and E. faecalis presented excellent performance. The results indicate the promising development of a new nano-antibiotic in which the functionalization potentiates the bacteriostatic action of AgNPs and vancomycin with greater efficacy against Gram-positive strains.

The SciQA Scientific Question Answering Benchmark for Scholarly Knowledge

Knowledge graphs have gained increasing popularity in the last decade in science and technology. However, knowledge graphs are currently relatively simple to moderate semantic structures that are mainly a collection of factual statements. Question answering (QA) benchmarks and systems were so far mainly geared towards encyclopedic knowledge graphs such as DBpedia and Wikidata. We present SciQA a scientific QA benchmark for scholarly knowledge. The benchmark leverages the Open Research Knowledge Graph (ORKG) which includes almost 170,000 resources describing research contributions of almost 15,000 scholarly articles from 709 research fields. Following a bottom-up methodology, we first manually developed a set of 100 complex questions that can be answered using this knowledge graph. Furthermore, we devised eight question templates with which we automatically generated further 2465 questions, that can also be answered with the ORKG. The questions cover a range of research fields and question types and are translated into corresponding SPARQL queries over the ORKG. Based on two preliminary evaluations, we show that the resulting SciQA benchmark represents a challenging task for next-generation QA systems. This task is part of the open competitions at the 22nd International Semantic Web Conference 2023 as the Scholarly Question Answering over Linked Data (QALD) Challenge.

Novel bottom-up methodology to build the lifecycle inventory of unit operations: the impact of macroscopic components

Novel bottom-up methodology to build the lifecycle inventory of unit operations: the impact of macroscopic components

Designing English Listening Materials for the 12th Grade Students of Paket C

This research was carried out to design English listening materials for the 12th-grade students of Paket C. What are the English listening material learning needs of Paket C students in the 12th grade? It was one of the two research questions that guided the study. How were the English listening materials for Paket C students in the 12th grade designed? Built on design This investigation was carried out using research. To gather data regarding the students' listening demands in EFL teaching, semi-structured interviews and open-ended questionnaires were used. Validations by media and material experts were also carried out. According to the results of the data analysis, Paket C pupils need English listening resources first. Second, the audio media was created using a bottom-up methodology while going through iterative design phases, including problem-solving analysis, media development, testing, and reflection. The tutor's book, the students' book, and the MP3 listening materials were the three products of the design procedures. In conclusion, the 12th-grade students of Paket C need English listening materials related to their activity/background/profession, future/material usefulness, educational background, surrounding environment, and life skill. All of the students need to aim to design English listening materials for the 12th-grade students of Paket C.

Evaluation of the Impact of Input-Data Resolution on Building-Energy Simulation Accuracy and Computational Load—A Case Study of a Low-Rise Office Building

Building-energy consumption is the primary aim of urban energy consumption, which can aid in optimization of building operation and management techniques, creating sustainable building and built environments. However, modellers’ understanding of the relationship between building-energy modelling (BEM) accuracy and computational load is still qualitative and deprived of accurate quantitative study. Based on a bottom-up engineering methodology, this study aims to quantitatively explore the effects of building-model input data with different resolution accuracies on energy simulation results, including evaluation of computational load. According to the actual parameters of the case-study building, 108 models with varying input resolution levels were developed to estimate hourly energy usage and annual mean ambient temperature. The results demonstrated that with input parameters at low resolution levels, geometric parameters such as exterior windows, interior windows, and shading exhibited significantly lower computational loads, resulting in reduced errors in the final simulation performance, whereas the occupancy schedule, thermal zoning, and HVAC configuration parameters exhibited significant declines in simulation performance and accuracy. This study presents a methodology applicable to the majority of low-rise, rectangular office structures. Future work would concentrate on carrying out comparison tests for different building forms and types while gradually improving the automation of the process to enable use of the appropriate accuracy level in assessing the crucial issue of energy-modelling input.

Analysis of Capped Silver Nanoparticles Combined with Imipenem against Different Susceptibility Profiles of Klebsiella pneumoniae

Klebsiella pneumoniae (K. pneumoniae) is an opportunistic bacterium that has drawn attention due to its resistance to carbapenem antibiotics. The treatment of patients with severe infections has been challenging. Thus, silver nanoparticles (AgNPs) have been applied for their antimicrobial effects. This work aims to analyze the synergistic effect of the carbapenem antibiotic Imipenem with AgNPs against different susceptibility clinical profiles of K. pneumoniae. The silver nanoparticles were synthesized by bottom-up methodology and capped with alpha-lipoic acid. Susceptibility tests were performed using four K. pneumoniae strains with different susceptibility profiles to Imipenem. The strains were induced to form a biofilm for 48 h. Crystal violet and Resazurin assays were performed to determine biofilm formation and minimal inhibitory concentration, respectively. The reduction in Imipenem concentration with the association of nanoparticles was found in all strains studied in planktonic form, and the synergism between silver nanoparticles and Imipenem was demonstrated through the analysis of the fractional inhibitory concentration index. The viability percentage was reduced at rates ≥80% in the biofilm analysis, characterized by the minimal biofilm inhibitory concentration. The study's proposed association resulted in inhibitory effects on different K. pneumoniae profiles, both in planktonic forms and biofilm, with peculiar behavior in the Imipenem-resistant profile.

A bottom-up building stock quantification methodology for construction minerals using Earth Observation. The case of Hanoi

A bottom-up building stock quantification methodology for construction minerals using Earth Observation. The case of Hanoi

Creating public value with municipal Wi-Fi networks: a bottom-up methodology

PurposeThe purpose of this paper is evaluate the public value of municipal Wi-Fi networks by examining their costs and benefits. Increasing attention has been focused on the digital divide, i.e. inequalities in digital access, use and benefits, to a lesser extent on technologies providing opportunities to overcome these inequalities. Different theoretical traditions have approached the problem of the digital divide, this research represents a synthesis by combining a bottom-up approach to calculating the benefits of municipal Wi-Fi networks with an in-depth analysis of the digital divide in Europe.Design/methodology/approachAfter a systematic literature review, the paper uses a bottom-up methodology to evaluate the public value of a municipal Wi-Fi network by quantifying its potential benefits and costs. In addition, it includes different types of users based on the access opportunities available to them. It develops different scenarios for these users depending on the connection alternatives and the digital skills available across European countries.FindingsBy using data from the euro-28, the paper shows that, in general, the private value of a municipal Wi-Fi network is negative, the public value is positive. However, a greater public value is depending on the extent to which the benefits can be attributed to expectations about the arrival and usage of e-government services.Research limitations/implicationsBased on the quantitative analysis, the authors suggest that municipal Wi-Fi networks can provide the potential to bridge the digital divide. To generate public value, these networks have to be driven by a strong need for e-government services.Practical implicationsHowever, important factors in the adoption of these services are related to digital skills available in the particular region.Social implicationsIn addition, public investment is required to stimulate the growth of broadband infrastructure in a complementary manner to enable public wireless networks.Originality/valueThe paper combines new insights into the cost calculations of municipal Wi-Fi networks with socioeconomic data on digital skills to examine different types of users.

Spatially resolved hourly traffic emission over megacity Delhi using advanced traffic flow data

Abstract. This paper presents a bottom-up methodology to estimate multi-pollutant hourly gridded on-road traffic emission using advanced traffic flow and speed data for Delhi. We have used the globally adopted COPERT (Computer Programme to Calculate Emissions from Road Transport) emission functions to calculate the emission as a function of speed for 127 vehicle categories. At first, the traffic volume and congestion (travel time delay) relation is applied to model the 24 h traffic speed and flow for all the major road links of Delhi. The modelled traffic flow and speed shows an anti-correlation behaviour having peak traffic and emissions in morning–evening rush hours. We estimated an annual emission of 1.82 Gg for PM (particulate matter), 0.94 Gg for BC (black carbon), 0.75 Gg for OM (organic matter), 221 Gg for CO (carbon monoxide), 56 Gg for NOx (oxides of nitrogen), 64 Gg for VOC (volatile organic compound), 0.28 Gg for NH3 (ammonia), 0.26 Gg for N2O (nitrous oxide) and 11.38 Gg for CH4 (methane) for 2018 with an uncertainty of 60 %–68 %. The hourly emission variation shows bimodal peaks corresponding to morning and evening rush hours and congestion. The minimum emission rates are estimated in the early morning hours whereas the maximum emissions occurred during the evening hours. Inner Delhi is found to have higher emission flux because of higher road density and relatively lower average speed. Petrol vehicles dominate emission share (>50 %) across all pollutants except PM, BC and NOx, and within them the 2W (two-wheeler motorcycles) are the major contributors. Diesel-fuelled vehicles contribute most of the PM emission. Diesel and CNG (compressed natural gas) vehicles have a substantial contribution in NOx emission. This study provides very detailed spatiotemporal emission maps for megacity Delhi, which can be used in air quality models for developing suitable strategies to reduce the traffic-related pollution. Moreover, the developed methodology is a step forward in developing real-time emission with the growing availability of real-time traffic data. The complete dataset is publicly available on Zenodo at https://doi.org/10.5281/zenodo.6553770 (Singh et al., 2022).

Carbon dots applications for development of sustainable technologies for food safety: A comprehensive review

This review describes the application of carbon dots in the development of sustainable technologies for food safety and quality. Carbon dots (CDs) are surface-functionalized and minuscule in size, with controlled fluorescence, high environmental sensitivity, and a range of remarkable photochemical properties. Green CDs are now the subject of extensive study due to their potential applications in a wide range of fields, such as nano sensing, bio imaging, and photo catalysis. Synthesizing CDs involves the top-down strategy, which includes splitting the bigger carbon molecule into nanoscale particles, and the bottom-up methodology, which involves producing CDs from small carbon units. The problems in the food supply chain are very prominent, from farm to fork that include chemical, microbiological and human hygiene. CDs have recently garnered interest because of the straightforward synthesis method, high biocompatibility, and potential for a variety of innovative applications. CDs were prepared from any carbon source, such as food, food waste, plants, chemicals, and graphene. CDs may be extracted naturally from some foods, such as honey, caramels, and sugar beet molasses. The rapid detection of dietary nutrients and toxins has sparked considerable attention, and nanomaterials-based fluorescence sensing has great promise for establishing exceptionally selective and sensitive identification procedures for food safety testing. Carbon dots have a promising future in fluorescence detection of contaminants due to their significant properties. Carbon dot sensors have capacity in the food sensing sector, since food samples include a variety of components that might create interferences, more innovative approaches to bind with CDs are necessary to develop specific sensing probes.

A Bottom-Up Methodology for the Fast Assessment of CNN Mappings on Energy-Efficient Accelerators

The execution of machine learning (ML) algorithms on resource-constrained embedded systems is very challenging in edge computing. To address this issue, ML accelerators are among the most efficient solutions. They are the result of aggressive architecture customization. Finding energy-efficient mappings of ML workloads on accelerators, however, is a very challenging task. In this paper, we propose a design methodology by combining different abstraction levels to quickly address the mapping of convolutional neural networks on ML accelerators. Starting from an open-source core adopting the RISC-V instruction set architecture, we define in RTL a more flexible and powerful multiply-and-accumulate (MAC) unit, compared to the native MAC unit. Our proposal contributes to improving the energy efficiency of the RISC-V cores of PULPino. To effectively evaluate its benefits at system level, while considering CNN execution, we build a corresponding analytical model in the Timeloop/Accelergy simulation and evaluation environment. This enables us to quickly explore CNN mappings on a typical RISC-V system-on-chip model, manufactured under the name of GAP8. The modeling flexibility offered by Timeloop makes it possible to easily evaluate our novel MAC unit in further CNN accelerator architectures such as Eyeriss and DianNao. Overall, the resulting bottom-up methodology assists designers in the efficient implementation of CNNs on ML accelerators by leveraging the accuracy and speed of the combined abstraction levels.

Antibacterial activity of silver nanoparticles functionalized with amikacin applied against multidrug-resistant acinetobacter baumannii

BackgroundMultidrug-resistant bacteria are one of the world's biggest health problems; therefore, improving the spectrum of action of antibiotics could be necessary to reverse this situation. Amikacin and silver salts have well-known antimicrobial properties. However, both drugs lost their effectiveness against some bacteria, such as Acinetobacter baumannii. This work aims to develop a nanodrug from silver nanoparticles (AgNPs) functionalized with Amikacin against multidrug-resistant Acinetobacter baumannii. MethodsAgNPs were produced using the bottom-up methodology and functionalized with Amikacin modified by the carbodiimide-based chemistry, forming AgNPs@Amikacin. Susceptibility tests were performed using Amikacin-resistant Acinetobacter baumannii strains to assess the bacteriostatic and bactericidal potential of the developed nanodrug. The clinical strains were induced to form a biofilm, and biomass quantification and the metabolic activity were determined. ResultsThe AgNPs have a hydrodynamic diameter of the particles with a bimodal distribution, with a size of 37.84 nm. The FT-IR spectrum of AgNPs@Amikacin exhibits vibrational modes corresponding to Amikacin, confirming the conjugation to AgNPs. Susceptibility testing demonstrated a minimal inhibitory and bactericidal concentration of < 0.5 µg/mL. The AgNPs@Amikacin reduced the biofilm metabolic activity of Acinetobacter baumannii at rates ≥ 50%, characterized by the minimal biofilm inhibition concentrations. ConclusionsResults demonstrate a promising development of a new nanodrug with lower concentrations, less toxicity, and greater efficacy against multidrug-resistant Acinetobacter baumannii.

A bottom‐up design methodology of neural min‐sum decoders for LDPC codes

It is known the belief propagation variants of linear codes can be readily unrolled as neural networks, after assigning learnable weights on the message-passing edges. Contrary to the conventional top-down training process, where the distillation occurs in the form of pruning or sharing when downsizing model is required, a new bottom-up design methodology to augment performance of the raw min-sum decoder of LDPC codes is proposed, by introducing incrementally a few parameters in the specific positions of corresponding neural network. Then a novel postprocessing method, devised to further improve performance, can cope with decoding failures effectively. In the training process, a simplified scheme of generating training data is presented via exploiting an approximation to the targeted mixture density, and it is found the evaluation of trained parameters converges after sufficient iterations, indicating its generality with an arbitrary designated number of iterations. Lastly, an extensive simulation of three codes carried on the AWGN or Rayleigh fading channels demonstrates the design reaches a good tradeoff of low-complexity and comparable decoding performance.

A novel bottom-up methodology for design and fabrication of three-dimensional braided hybrid composites based on the law of yarn routing and grouping

A hybrid is an effective means to improve the comprehensive properties of composites. In the current article, by investigating the yarn routing and grouping law in three-dimensional braiding, a novel bottom-up methodology for the design and fabrication of three-dimensional braided hybrid composites is proposed based on the [ m, m] hybrid unit. Three-dimensional braided hybrid composites with different sizes of hybrid unit were prepared and drop-hammer based impact tests were conducted to study the composites' dynamic mechanical performances. It was found that the three-dimensional braided hybrid composites based on the bottom-up methodology present much better structural integrity and toughness than conventional ply-stacked hybrid counterparts and significant dependence of mechanical performances on the size of hybrid unit. We found that the smaller the size of hybrid unit, the better the mechanical performance. The results demonstrated the feasibility and effectiveness of the proposed bottom-up methodology and could enable the design and fabrication of three-dimensional braided preforms and composites with certain well designed structures and functions.

Sea Port SO2 Atmospheric Emissions Influence on Air Quality and Exposure at Veracruz, Mexico

In this work, we identify the current atmospheric sulfur dioxide emissions of the Veracruz port, an important Mexican seaport experiencing rapid growth, and its influence on the surrounding areas. Sulfur dioxide emissions based on port activity, as well as meteorology and air quality simulations, are used to assess the impact. It was found that using marine fuel with low sulfur content reduces emissions by 88%. Atmospheric emission estimates based on the bottom-up methodology range from 3 to 7 Mg/year and can negatively impact air quality up to 3 km downwind. After evaluating different characteristics of vessels in CALPUFF, it was found that maximum sulfur dioxide concentrations ranging between 50 and 88 µg/m3 for a 24-h average occurred 500 m from the port. During 2019, five days had unsatisfactory air quality. The combination of a shallow planetary boundary layer, low wind speed, and large atmospheric emissions significantly degraded local air quality.

Greenhouse gas emissions of an outpatient care service: a cost-based approach

IntroductionClimate change is already having an impact on global health and will continue to do so even more. Heat waves and extreme weather events are only part of the impact. Adapting health services to these threats is only partially possible, so another focus should be on mitigating climate change by minimising greenhouse gas emissions. In this context, health care can play an important role. However, evidence about greenhouse gas emission hotspots and alternative action to mitigate greenhouse gas emissions is needed for the shift to a climate-friendly health system. MethodsIn this paper, the greenhouse gas emissions of an outpatient care service will be calculated. On the one hand, focal points of the emissions will be identified and the effects of climate-friendly measures calculated. In order to calculate a comprehensive footprint, a hybrid approach was chosen in which emissions from electricity, gas and fuels are determined on the basis of quantities, and emissions resulting from the production of consumer goods are calculated using cost-based emission factors. The expenditure and consumption data required come from a care service in Lower Saxony providing for 132 people in need of care. ResultsThe outpatient care service emitted a total of 37,258 kg CO2eq in 2018, i.e. roughly 282 kg CO2eq per year and person in need of care. The production (15%) and combustion of fuels (68%) accounted for the largest share of 73%. By switching to diesel vehicles, the care service could save 7% of the annual greenhouse gas emissions and by switching to electric vehicles up to 30%. DiscussionThe study shows that the outpatient care service produces greenhouse gas emissions of about 282 kg CO2eq per year and person in need of care, which is a relevant amount given the average per capita emission of 7.9 kg CO2 in Germany. However, these emissions can be reduced by more than half by making the relatively easy switch to electric cars.Limitations of the study relate to potential inaccuracies of the cost-based emission factors and the lack of information about the kilometers driven and the fuel consumed. ConclusionThe majority of the emissions of an ambulatory care service comes from the production and combustion of fuels. However, this source can be significantly reduced by switching to modern technologies. To validate the results of this study, further studies should be conducted, preferably with a bottom-up methodology.

Dual pulsed laser deposition of Ag nanoparticles on calcium phosphate coatings for biomedical applications

Pulsed laser deposition (PLD) represents a promising bottom-up methodology for the synthesis and transference of nanoparticles to the surface of a biomedical device. Silver (Ag) nanoparticles directly incorporated on the metallic implant emerge as an alternative strategy for local action against prosthetic joint-associated infections. In the present research, a dual sequential PLD process is proposed to obtain a bilayer coating with (1) a bio-derived calcium phosphate (CaP) layer, to provide osteointegrative properties and (2) the controlled growth of the Ag nanoparticles over it, ranging the number of laser pulses from 100 to 500. The characterization by SEM, EDS, TEM, XPS and AFM revealed the uniform deposit of Ag rounded nanoparticles, with a narrow mean size distribution, in the original non-oxidized metallic state. Moreover, given the evidences from XPS and AFM techniques, the occurrence of a coalescence phenomenon from 400 pulses onwards was proposed together with the expected positive linear relation between the number of pulses and Ag contribution with a deposition rate of 0.05 at. % of Ag per pulse. Conversely, the decrease in roughness as the Ag content increased was also verified. Finally, the expected bacteriostatic activity for these PLD deposited metallic state Ag nanoparticles against the bacterial strain Staphylococcus aureus was confirmed. Moreover, the evaluation of the osteoblast-like MG-63 cells viability on the Ag(100–500)-CaP coatings revealed a significant increased proliferation (p > 0.05) on the Ag100-CaP coating compared to the control (Ag0-CaP). When same coating was evaluated against S. aureus the effect was not significant. The possibility of modulating the amount of nanoparticles in the bilayer coating to obtain a greater or lesser effect in combination with CaP was revealed.

Tiered prediction models for port vessel emissions inventories

Albeit its importance, a large number of port authorities do not provide continuous or publicly available air emissions inventories (EIs) and thereby obscure the emissions contribution of ports. This is caused by, e.g., the economic effort generated by obtaining data. Therefore, the performance of abatement measures is not monitored and projected, which is specifically disadvantageous concerning top contributors such as container ships. To mitigate this issue, in this paper we propose port vessel EI prediction models by exploring the combination of different machine-learning algorithms, data from the one-off application of an activity-based bottom-up methodology and vessel-characteristics data. The results for this specific case show that prediction models enable acceptable trade-offs between the prediction performance and data requirements, promoting the creation of EIs.

Distinctive sensing nanotool for free and nanoencapsulated quercetin discrimination based on S,N co-doped graphene dots

A selective and sensitive fluorescent nanoprobe (sulfur and nitrogen co-doped graphene quantum dots, S,N-GQDs) was designed for both detection and discrimination between free and quercetin-loaded nanoemulsion in food samples of diverse nature. Quercetin nanoemulsions (Q-NEs) were synthesized by a phase inversion temperature (PIT) procedure, while S,N-GQDs were synthesized using a bottom-up methodology by means of simple hydrothermal treatment of citric acid and cysteamine. Both synthetized nanomaterials (analyte and fluorescent probe), were carefully characterized through advanced spectroscopic and high-resolution microscopic techniques. It was observed that fluorescence intensity of S,N-GQDs could be markedly and distinctively quenched by the addition of both quercetin forms through inner filter effect (IFE) mechanisms, exhibiting static quenching events for free quercetin and Q-NEs but with a characteristic 13 nm red-shift spectra in presence of Q-NEs. Linear dynamic ranges between 0.05 and 10 mg L−1 and 0.025–70 mg L−1, with detection limits of 17 and 8 μg L−1 were revealed for free and nanoquercetin, respectively. After nanostructural and physic-chemical optimization, the discrimination strategy was metrologically validated and applied to nutraceutical supplements containing nanoencapsulated quercetin and on diverse free quercetin products such as onion peels and dietary supplements. Accuracy and reliability were proved by means of a statistical comparison with the results obtained by a μHPLC-DAD method (paired Student's t-test at 95% confidence level). The method provides the exciting prospect of analyzing new designed nanoencapsulated bioactives without altering their native nanostructure, as well as being able to accomplish the challenge to distinguish between both forms of quercetin.

Photodegradation of oxolinic acid in aquaculture effluents under solar irradiation: is it possible to enhance efficiency by the use of TiO2/carbon quantum dots composites?

Antibiotics, such as oxolinic acid (OXA), in aquaculture effluents contribute to the dissemination of antimicrobial resistance, which makes it urgent to develop efficient and sustainable processes for their removal. Aiming a photocatalytic degradation under solar radiation, different carbon quantum dots (CQDs) were produced in this work through a bottom-up hydrothermal methodology and incorporated into TiO2 by a simple calcination method. A total of thirteen materials were synthesized and tested for OXA photocatalytic removal from synthetic and real matrices. Among them, CQDs produced with citric acid and incorporated into TiO2 at 4% (w/w) (TiO2/CQDs-CA 4% (w/w)) were the most efficient photocatalysts, providing an OXA half-life time (t1/2) decrease of 91%, 79% and 85% in phosphate buffer solution (PBS), synthetic sea salts (SSS) and brackish aquaculture effluent (BAE), respectively. Therefore, the herein synthesized TiO2/CQDs-CA 4% (w/w) composites have shown to be promising materials for a sustainable solar-driven removal of antibiotics from aquaculture effluents.