Competitive Routes Research Articles

Implementation of Flight Fare Prediction System Using Machine Learning

Abstract: The Flight ticket prices increase or decrease every now and then depending on various factors like timing of the flights, destination, duration of flights. In the proposed system a predictive model will be created by applying machine learning algorithms to the collected historical data of flights. Optimal timing for airline ticket purchasing from the consumer’s perspective is challenging principally because buyers have insufficient information for reasoning about future price movements. In this project we majorly targeted to uncover underlying trends of flight prices in India using historical data and also to suggest the best time to buy a flight ticket. The project implements the validations or contradictions towards myths regarding the airline industry, a comparison study among various models in predicting the optimal time to buy the flight ticket and the amount that can be saved if done so. Remarkably, the trends of the prices are highly sensitive to the route, month of departure, day of departure, time of departure, whether the day of departure is a holiday and airline carrier. Highly competitive routes like most business routes (tier 1 to tier 1 cities like Mumbai-Delhi) had a non-decreasing trend where prices increased as days to departure decreased, however other routes (tier 1 to tier 2 cities like Delhi - Guwahati) had a specific time frame where the prices are minimum. Moreover, the data also uncovered two basic categories of airline carriers operating in India – the economical group and the luxurious group, and in most cases, the minimum priced flight was a member of the economical group. The data also validated the fact that, there are certain time-periods of the day where the prices are expected to be maximum. The scope of the project can be extensively extended across the various routes to make significant savings on the purchase of flight prices across the Indian Domestic Airline market. Keywords: Flight ticket, Optimal timing, historical data, competitive routes, Indian Domestic Airline market.

Flight Fare Prediction System Using Machine Learning

Abstract: The Flight ticket prices increase or decrease every now and then depending on various factors like timing of the flights, destination, duration of flights. In the proposed system a predictive model will be created by applying machine learning algorithms to the collected historical data of flights. Optimal timing for airline ticket purchasing from the consumer’s perspective is challenging principally because buyers have insufficient information for reasoning about future price movements. In this project we majorly targeted to uncover underlying trends of flight prices in India using historical data and also to suggest the best time to buy a flight ticket. The project implements the validations or contradictions towards myths regarding the airline industry, a comparison study among various models in predicting the optimal time to buy the flight ticket and the amount that can be saved if done so. Remarkably, the trends of the prices are highly sensitive to the route, month of departure, day of departure, time of departure, whether the day of departure is a holiday and airline carrier. Highly competitive routes like most business routes (tier 1 to tier 1 cities like Mumbai-Delhi) had a non-decreasing trend where prices increased as days to departure decreased, however other routes (tier 1 to tier 2 cities like Delhi - Guwahati) had a specific time frame where the prices are minimum. Moreover, the data also uncovered two basic categories of airline carriers operating in India – the economical group and the luxurious group, and in most cases, the minimum priced flight was a member of the economical group. The data also validated the fact that, there are certain time-periods of the day where the prices are expected to be maximum. The scope of the project can be extensively extended across the various routes to make significant savings on the purchase of flight prices across the Indian Domestic Airline market. Keywords: Flight ticket, Optimal timing, historical data, competitive routes, Indian Domestic Airline market

Assessment of hydrogen production from municipal solid wastes as competitive route to produce low-carbon H2

An economic and CO2 emission impact assessment of the production of H2 from municipal solid waste in the two configurations of retrofitting an existing waste to energy plant with an electrolysis unit (WtE + El) and of hydrogen production via waste gasification (WtH2) is made with respect to reference cases of H2 production by steam reforming of methane (SMR) or of water electrolysis (El). The results are analyzed with reference to two scenarios depending on whether the fate of waste disposal emissions for SMR and El is accounted. The costs of H2 production as a function of waste gate fee and CO2 taxation as well as the CO2 emissions for both scenarios and the four cases of H2 production analyzed are reported. The results show that produce H2 from a WtE plant hybridized with an electrolyzer could be economic only when the plant is free from depreciation costs and no CO2 taxation exists. Conversely, WtH2 solution results preferable when CO2 taxation will be applied to the non-biogenic fraction of waste. Conditions when WtH2 may results competitive to SMR are defined, in terms of both cost of production and CO2 emissions. With respect to El case, WtH2 results more competitive under the assumption made in terms of combined costs and CO2 emissions.

Out of the spotlight: Four years of Italian coach market prices

Analogous to Germany and France, Italian coach market radically changed after liberalisation (2014). Liberalisation led to new routes, increased frequencies, mergers, and withdrawals. The paper analyses market trends from four years of real ticket prices collected through collaboration with www.checkmybus.it. The dataset, consisting of monthly average prices and the number of clicks by company and by city-pair, is enriched with spatial information, including the separation of airport routes. Results show that sub-national markets had different trends, with the growth of offer on routes linked to network expansion of the early liberalisation slowing down. Contrarily, the historical routes to the Centre and South remain stable. Interestingly, larger (Top-5) companies' prices are below market average up to 5–10% less. Smaller companies operate often on niche routes, with fewer economies of scale and thus maintain higher prices. This trend switched during the COVID pandemic. A further comparison with rail prices showed that coaches were able to reduce the price gap at least with conventional trains, from −50% (average for 2017–2020) to −20% for the second semester of 2020. This is a sign of the ability of the coach sector to adapt to the shock, by reducing capacity and concentrating on more competitive routes.

Thermodynamic analysis of titanium dioxide-based isothermal methanothermal and carbothermal redox cycles for solar fuel production

Due to the less efficiency-penalty and avoidance of thermal stress resulting from temperature swings, isothermal thermochemical redox cycle has emerged as a promising way to produce solar fuels. However, the isothermal thermochemical cycles based on the currently reported metal oxides have not shown a competitive theoretical solar-to-fuel efficiency. Herein, titanium dioxide-based isothermal methanothermal redox cycle and carbothermal redox cycle for efficient solar fuel production have been proposed and thoroughly evaluated thermodynamically. The calculations suggest that the reactant ratio of 0.5 is beneficial for oxygen release and fuel selectivity in the reduction step. Excessive reducing agents could cause the generation of the by-product titanium carbide, resulting in the loss of redox capacity. Attributing to the considerable thermodynamic driving force for water splitting, the reduced titanium dioxide could be almost fully reoxidized even at high temperatures ⩾1600 K without excess water. As expected, the efficiency evaluation indicates that the studied isothermal redox cycles are more thermodynamically favorable than the non-isothermal ones. Furthermore, according to the efficiency optimization strategy, the methanothermal and carbothermal redox cycles should be performed at the reactant ratios of 0.4 (reduction step) and 0.5 (water-splitting step) under the isothermal operating at 1500 K and 1600 K, respectively, to achieve the highest solar-to-fuel efficiencies of 40.0% and 35.7% without heat recuperation. The results indicate that the titanium dioxide-based isothermal methanothermal and carbothermal redox cycles both have the potential of becoming competitive routes for solar fuel production.

A new route to produce 52gMn with high purity for MultiModal Imaging

The 52gMn radionuclide is suitable for the innovative MultiModal Imaging technique, and in particular for a PET/MRI scan, due to its physical properties. The standard cyclotron-based production of 52gMn relies on the nuclear reaction NatCr(p,x)52gMn, but we have investigated theoretically the possibility of an alternative and competitive route, the reaction NatV(α,x)52gMn, which has not been considered for this purpose so far. By using the nuclear reaction code TALYS, we found some discrepancies between the theoretical calculations of the cross sections and the corresponding experimental data. Therefore we tuned the parameters governing the nuclear level densities in the microscopic models implemented in TALYS, thus improving the agreement with the data. Then, by studying the cross sections for 52gMn and its contaminants, we have identified an optimal energy window for the production of high purity 52gMn, around 40 MeV. We have also calculated the time evolution of the number of nuclei of the different Mn isotopes, for an irradiation in this energy window, finding that this route is expected to lead to a higher yield and Radionuclidic Purity with respect to the standard reaction with NatCr. The study suggests the reaction NatV(α,x)52gMn as a promising alternative route for the production of 52gMn.

A single rapid route synthesis of magnetite/chitosan nanocomposite: Competitive study

At last decides, the modification of synthesis protocol towards shorter reaction time, fewer steps, and lower resources cost was needed. The synthesis of magnetite (Fe3O4) polymer nanocomposite is heavily studied nowadays due to its promising applications. In this study, magnetite chitosan nanocomposite was synthesized through two competitive routes; a new single route synthesis based on co-precipitation at hydrothermal conditions, and the second route a conventional multi-synthetic route based on using the blending solution method after magnetite nanoparticles synthesis by the co-precipitation method of magnetite. The synthesized Fe3O4 and its nanocomposites are characterized by several techniques, including Fourier transition infrared spectroscopy (FTIR), X-ray diffraction (XRD), scanning electron microscopy (SEM), and vibration sample magnetometer (VSM). The results showed magnetite polymer nanocomposite synthesized via a single synthetic route had less particle size, more distribution in the chitosan matrix, and higher magnetization saturation than that synthesized via a multi-synthetic route. Adsorption of Rodamine 6G dye on magnetite chitosan nanocomposite was studied in different parameters. The adsorption results showed a rapid process following the Tempkin isotherm.

Assessment of Hydrogen Production from Municipal Solid Wastes as Competitive Route to Produce Low-Carbon H2

Assessment of Hydrogen Production from Municipal Solid Wastes as Competitive Route to Produce Low-Carbon H2

L-tyrosine metabolic pathway in microorganisms and its application in the biosynthesis of plant-derived natural products

L-tyrosine, an aromatic amino acid, is an important upstream precursor for the synthesis of a series of valuable natural products such as flavonoids and phenolic acids. In recent years, regulation of the L-tyrosine metabolic pathway has been devoted to enhancing the production of L-tyrosine and the derived bioactive compounds in microorganisms, usually by increasing the supply of precursors, blocking competitive routes, and modulating the transport system. Here, we reviewed the strategies to promote L-tyrosine production in microbial hosts and the common strategies to produce bioactive compounds in engineered Escherichia coli and Saccharomyces cerevisiae to better understand and utilize the L-tyrosine metabolic pathway for microbial overproduction of diverse valuable aromatic compounds in the future.

Rival or comrade? A systematic review and conceptual framework of when and why the powerful act prosocially or antisocially towards each other

AbstractWe present a systematic review of the literature on power and its interpersonal consequences. Our review, comprising 339 studies published in 145 research articles, shows that this line of research has primarily examined how powerholders attend to and act towards powerless individuals, or others in general. We therefore know surprisingly little about how powerholders attend to and act towards other powerholders. To address this issue, we present a conceptual framework that outlines how an actor’s power interacts with a target’s power to influence prosocial and antisocial beliefs, attitudes, and behaviors. We identify two routes in the literature detailing how powerholders respond to one another. First, building on rivalry literature, we present a competitive route suggesting that powerholders rival each other and engage in conflict. Second, building on social identity and social dominance literature, we present a harmonious route suggesting that powerful peers will show compassion and care for each other. Finally, we bring forth suggestions for how future research could test these two perspectives, by presenting moderators that determine when each of these two routes is activated. In doing so, we offer important implications for the power literature and open a new line of inquiry for future research.

Coordinated Capacity Reductions and Public Communication in the Airline Industry

Abstract We investigate the allegation that legacy US airlines communicated via earnings calls to coordinate with other legacy airlines in offering fewer seats on competitive routes. To this end, we first use text analytics to build a novel dataset on communication among airlines about their capacity choices. Estimates from our preferred specification show that the number of offered seats is 2$\%$ lower when all legacy airlines in a market discuss the concept of “capacity discipline.” We verify that this reduction materializes only when legacy airlines communicate concurrently, and that it cannot be explained by other possibilities, including that airlines are simply announcing to investors their unilateral plans to reduce capacity, and then following through on those announcements.

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The issues of implementation of long-term goals of sustainable development of sea passenger transportation, achievement of transportation results, overcoming the negative impact of factors of unstable external environment, which are determined by the chosen course laid down in the basis of strategic management of ferry transportation and choice of route directions, are investigated in the paper. The study indicates that despite the negative impact of COVID-19 and the resulting delayed passenger demand for cruise services, the potential of the maritime ferry and cruise market is very high. It is noted that since 2021 there is a gradual process of recovery of route networks, which takes place in different regions with different dynamics. Therefore, the goals of ferry companies are to implement several strategic planning tasks, among which the task of designing the most efficient new route network is relevant, while companies can start to implement route networks and destinations based on the existing route networks (e. g. networks and destinations of the Baltic Sea) for 2019. It is emphasized that due to the new possibility to attract additional passenger traffic, detailed research and modelling of different options is needed. The Baltic Sea region is chosen as the object for the study, since the local mobility of passageways makes it possible to renew the routes in the shortest possible time. The data for different seas, characterizing the intervals of decline and justifying the necessity of innovations on the basis of new competitive routes creation, are presented in the study. The subject of the study is routes and route networks of the seas regions. The use of models in the form of graphs and algorithms, such as Dijkstra’s algorithm, is proposed for modelling different variants of sea ferry routes architecture. The new ferry route network model is implemented in the J-Circos software environment for the subsequent construction of various intensity diagram options. Due to the flexibility of the interfaces and the software environment it is possible to combine the existing networks in 2019 and the proposed new routes in a single information field. In this way, a new possibility to assess the position of a ferry company on the passenger market and to evaluate the quantitative indicators in relation to the other ferry and cruise companies is considered in the paper. The proposed solutions are included in a separate decision-making flowchart for selecting a promotion strategy in the sea region ferry market. The solutions presented have versatility, the methodology and implementation can also be applied to the other sea regions. A new possibility of representing evolutionary changes in the route networks, which also provides an opportunity to further improve the quality of strategic planning and promotion decision-making, forming a separate area of analytical work of a maritime ferry company, is considered.

Biomass-Based Carbon-Supported Sulfate Catalyst for Efficient Synthesis of Dimethoxymethane from Direct Oxidation of Dimethyl Ether

The synthesis of dimethoxymethane (DMM) from direct oxidation of dimethyl ether (DME) is a green and competitive route with good atomic economy and low carbon emission and is also an urgent need. In this work, biomass-based carbon-supported sulfate catalysts were designed and prepared for the efficient synthesis of DMM from DME oxidation. The prepared carbon support from cellulose displayed much larger specific surface area and a developed microporous structure, which effectively benefited a high dispersion of sulfate components, leading to mainly weak acid sites and more oxygen functional groups on the catalyst surface. The Ti(SO4)2/PC-H2SO4 catalyst exhibits excellent performance for DME oxidation with DMM1-2 selectivity up to 96.7%, and DMM selectivity reaches 89.1%, notably higher than that of previously reported results. The distinctive surface structure and chemical properties of the carbon support have important impacts on the dispersion state of sulfate species, affecting the acidic and redox properties of the catalysts.

Impact of As-Prepared and Purifıed Multi-Walled Carbon Nanotubeson the Liquid-Phase Aerobic Oxidatıon of Hydrocarbons

The article presents simple kinetic approaches to study the effect of multi-walled carbon nanotubes (MWCNTs) additives on the aerobic oxidation of hydrocarbons and to propose real acceptable mechanisms of the process. The aerobic liquid phase low-temperature oxidation of ethylbenzene conducted in the presence of multi-walled carbon nanotubes has been used as a model pattern. Kinetic analysis established the catalytic action associated with the presence of the iron compounds in inner channels of MWCNTs. These compounds are identified as ferric carbides provoking decomposition of the ethylbenzene hydroperoxide and thereby suppressing the competitive route of alky-peroxide radicals addition to the nanocarbon cage. Thus the reaction finally proceeds in the autocatalytic mode.Contradictory conclusions on the effect of CNTs on the oxidation chain processes existing in the literature are associated with the lack of control over nature and content of metal impurities in channels of nanotubes.

Enhancement of Patchoulol Production in Escherichia coli via Multiple Engineering Strategies.

As a natural sesquiterpene compound with numerous biological activities, patchoulol has extensive applications in the cosmetic industry and potential usage in pharmaceuticals. Although several patchoulol-producing microbial strains have been constructed, the low productivity still hampers large-scale fermentation. Escherichia coli possesses the ease of genetic manipulation and simple nutritional requirements and does not comprise competing pathways for the farnesyl diphosphate (FPP) precursor, showing its potential for patchoulol biosynthesis. Here, combinatorial strategies were applied to produce patchoulol in E. coli. The initial strain was constructed, and it produced 14 mg/L patchoulol after fermentation optimization. Patchoulol synthase (PTS) was engineered by semirational design, resulting in improved substrate binding affinity and a patchoulol titer of 40.3 mg/L; the patchoulol titer reached 66.2 mg/L after fusing of PTS with FPP synthase. To further improve the patchoulol production, the genome of an efficient chassis strain was engineered by deleting the competitive routes for acetate, lactate, ethanol, and succinate synthesis and cumulatively enhancing the expression of efflux transporters, which improved patchoulol production to 338.6 mg/L. When tested in a bioreactor, the patchoulol titer and productivity were further improved to 970.1 mg/L and 199 mg/L/d, respectively, and were among the highest levels reported using mineral salt medium.

Deciphering Competitive Routes for Nickel‐Based Nanoparticle Electrodeposition by an Operando Optical Monitoring

AbstractElectrodeposition of earth‐abundant iron group metals such as nickel is difficult to characterize by simple electrochemical analyses since the reduction of their metal salts often competes with inhibiting reactions. This makes the mechanistic interpretation sometimes contradictory, preventing unambiguous predictions about the nature and structure of the electrodeposited material. Herein, the complexity of Ni nanoparticles (NPs) electrodeposition on indium tin oxide (ITO) is unraveled operando and at a single entity NP level by optical microscopy correlated to ex situ SEM imaging. Our correlative approach allows differentiating the dynamics of formation of two different NP populations, metallic Ni and Ni(OH)2 with a <25 nm limit of detection, their formation being ruled by the competition between Ni2+ and water reduction. At the single NP level this results in a self‐terminated growth, an information which is most often hidden in ensemble averaged measurements.

Deciphering Competitive Routes for Nickel-Based Nanoparticle Electrodeposition by an Operando Optical Monitoring.

Electrodeposition of earth-abundant iron group metals such as nickel is difficult to characterize by simple electrochemical analyses since the reduction of their metal salts often competes with inhibiting reactions. This makes the mechanistic interpretation sometimes contradictory, preventing unambiguous predictions about the nature and structure of the electrodeposited material. Herein, the complexity of Ni nanoparticles (NPs) electrodeposition on indium tin oxide (ITO) is unraveled operando and at a single entity NP level by optical microscopy correlated to ex situ SEM imaging. Our correlative approach allows differentiating the dynamics of formation of two different NP populations, metallic Ni and Ni(OH)2 with a <25 nm limit of detection, their formation being ruled by the competition between Ni2+ and water reduction. At the single NP level this results in a self-terminated growth, an information which is most often hidden in ensemble averaged measurements.

Large-Scale de novo Oligonucleotide Synthesis for Whole-Genome Synthesis and Data Storage: Challenges and Opportunities.

Over the past decades, remarkable progress on phosphoramidite chemistry-based large-scale de novo oligonucleotide synthesis has been achieved, enabling numerous novel and exciting applications. Among them, de novo genome synthesis and DNA data storage are striking. However, to make these two applications more practical, the synthesis length, speed, cost, and throughput require vast improvements, which is a challenge to be met by the phosphoramidite chemistry. Harnessing the power of enzymes, the recently emerged enzymatic methods provide a competitive route to overcome this challenge. In this review, we first summarize the status of large-scale oligonucleotide synthesis technologies including the basic methodology and large-scale synthesis approaches, with special focus on the emerging enzymatic methods. Afterward, we discuss the opportunities and challenges of large-scale oligonucleotide synthesis on de novo genome synthesis and DNA data storage respectively.

Production of bio-ethanol by consecutive hydrogenolysis of corn-stalk cellulose

Current bio-ethanol production entails the enzymatic depolymerization of cellulose, but this process shows low efficiency and poor economy. In this work, we developed a consecutive aqueous hydrogenolysis process for the conversion of corn-stalk cellulose to produce a relatively high concentration of bio-ethanol (6.1 wt%) without humin formation. A high yield of cellulose (ca. 50 wt%) is extracted from corn stalk using a green solvent (80 wt% 1,4-butanediol) without destroying the structure of the lignin. The first hydrothermal hydrogenolysis step uses a Ni–WOx/SiO2 catalyst to convert the high cumulative concentration of cellulose (30 wt%) into a polyol mixture with a 56.5 C% yield of ethylene glycol (EG). The original polyol mixture is then subjected to subsequent selective aqueous-phase hydrogenolysis of the C–O bond to produce bioethanol (75% conversion, 84 C% selectivity) over the modified hydrothermally stable Cu catalysts. The added Ni component favors the good dispersion of Cu nanoparticles, and the incorporated Au3+ helps to stabilize the active Cu0-Cu+ species. This multi-functional catalytic process provides an economically competitive route for the production of cellulosic ethanol from raw lignocellulose.

Spatially Characterizing Major Airline Alliances: A Network Analysis

An airline alliance is a group of member airlines that seek to achieve the same goals through routes and airports. Hence, airports’ connectivity plays an essential role in understanding the linkage between different markets, especially the impact of neighboring airports on focal airports. An airline alliance airport network (AAAN) comprises airports as nodes and routes as edges. It could reflect a clear collaborative proportion within AAAN and competitive routes between AAANs. Recent studies adopted an airport- or route-centric perspective to evaluate the relationship between airline alliances and their member airlines; meanwhile, they mentioned that an airport community could provide valuable air transportation information because it considers the entire network structure, including the impacts of the direct and indirect routes. The objectives are to identify spatial patterns of market region in an airline alliance and characterize the differences among airline alliances (Oneworld, Star Alliance, and SkyTeam), including regions of collaboration, competition, and dominance. Our results show that Star Alliance has the highest collaboration and international market dominance among three airline alliances. The most competitive regions are Asia-Pacific, West Asia, Europe, and North and Central America. The network approach we proposed identifies market characteristics, highlights the region of market advantages in the airline alliance, and also provides more insights for airline and airline alliances to extend their market share or service areas.