Spread Of Solutions Research Articles

A sustainable vaccine supply-production-distribution network with heterologous and homologous vaccination strategies: Bi-objective optimization

Heterologous and homologous Coronavirus Disease 2019 (COVID-19) vaccination against Severe Acute Respiratory Syndrome (SARS)-CoV-2 are robust and proactively adaptable strategies. However, there is still a lack of appropriate mathematical models for integrating vaccination strategies into the vaccine supply chain network. This study develops a supply-production-distribution-inventory-allocation problem in the Sustainable Vaccine Supply-Production-Distribution Network (SVSPDN) to fill this gap for the first time. The outstanding novelties of this research are prioritizing vaccines and sequencing injection doses to increase vaccination effectiveness. In addition, the remarkable new contribution of the proposed mathematical model is the design of new bi-objective, multi-dose, multi-level, and multi-period to ensure the sustainability performance of the entire network. This aim is achievable by minimizing the cost of supplying, producing, and distributing vaccines and fulfilling social goals by maximizing vaccination effectiveness. Also, a scenario-based robust stochastic optimization approach is presented to handle uncertainties. Since the SVSPDN design is an NP-hard problem, to solve the proposed mathematical model, three Pareto-based evolutionary algorithms, including Non-Dominated Sorting Genetic Algorithm II (NSGA-II), Multi-Objective Particle Swarm Optimization (MOPSO), and Multi-Objective Gray Wolf Optimizer (MOGWO), are applied. The Taguchi design method is applied to tuning the parameters due to the sensitivity of meta-heuristic algorithms to input parameters. Then, a comparison is performed using four assessment metrics, including the Number of Pareto Solutions (NPS), Diversification Matrix (DM), Mean Ideal Distance (MID), Spread of Non-Dominance Solutions (SNS), and Computation Time (CT). The results reveal that the NSGA-II and MOGWO algorithms have performances that are very close to each other. However, MOGWO performs better in tackling the problem and is superior to the NSGA-II and MOPSO regarding assessment metrics and computation time. A case study of Iran is investigated to indicate the efficiency and applicability of the proposed model. Finally, sensitivity analyses, managerial insights, and practical implications are discussed.

Laboratory and numerical investigations on land-sourced solute transport in coastal fractured aquifers

Land-based pollutants threaten coastal aquifers, highlighting the need to protect groundwater and nearshore marine ecosystems. While aquifer heterogeneity has been recognized as a significant factor affecting solute behavior, the impact of fractures on land-sourced solute transport in coastal aquifers remains unclear. This study attempted to address this issue through laboratory experiments and discrete fracture matrix (DFM) models. The impact of horizontal fractures on the temporal and spatial characteristics of solute transport, spreading, and discharge under seawater intrusion was analyzed based on variations in fracture position and length. The results show that fractures/low-velocity zones (LVZ) can accelerate/delay solutes, dividing them into different transport modes and enhancing/prolonging their spreading/discharge duration. Changes in fracture position and length also affect its transport acceleration and path deviation abilities, which ultimately determine when solute discharge occurs. The mixing zone and unsaturated zone, in addition to the LVZ, hinder solute transport, reducing the rate and delaying the end of solute discharge. Meanwhile, fractures facilitate solute transport into the saltwater wedge, expanding the solute discharge zone. However, if solutes are initially within the LVZ, their entry into the fracture rely on their distance from the fracture's near-land edge and the size of the fracture's convergence zone.

Designing a new sustainable healthcare network considering the COVID-19 pandemic: Artificial intelligence-based solutions

The COVID-19 pandemic, which is still spreading its new mutations all around the world, is considered a healthcare challenge around the world. The best approach to forestall this pandemic is to avoid exposure to the virus. Therefore, medical protective equipment is essential for fighting this pandemic. This underlines the chief role of having a sustainable supply chain network (SCN) for producing and distributing personal protective equipment to avoid shortage and augmenting costs. The reality, however, is that the COVID-19 pandemic leads to many developments in countries and this study is another step for these purposes. This research developsa multi-period, multi-objective, multi-echelon, and multi-product medical protective equipment sustainable SCN considering the production, distribution, allocation, and inventory with “risk pooling” strategy effect with the aim of filling the existing gaps in health SCN research during the COVID-19 pandemic. By applying the risk pooling strategy, lower inventory levels or higher service levels can be achieved without increasing inventory costs. This model explores the possibility of lateral transshipments between distribution centers, as a way to increase the reliability of SCN performance. We model a new production, inventory, distribution, location, and allocation problem and consider four objectives for our suggested model (i) minimizing total SCN costs, (ii) minimizing environmental effects, (iii) minimizing social impacts, and (iv) maximizing the reliability of demand delivery. The proposedmodel simultaneously examines all three dimensions of sustainability (economic, environmental, and social) as well as the reliability of demand delivery. Considering all of these decisions and assumptions brings the studied problem closer to reality. We employ various algorithms for solving our developed model with different sizes: the improved version of the augmented ε-constraint (AUGMECON2) algorithm for small and medium-sized problems and two meta-heuristic algorithms, i.e., Multi-Objective Whale Optimization Algorithm (MOWOA) and Multi-Objective Variable Neighborhood Search (MOVNS) algorithm, for large-sized ones. The Taguchi approach is used to tune the parameters of meta-heuristic algorithms, and a comparison is performed using four evaluation metrics: Mean Ideal Distance (MID), Number of Pareto Solutions (NPS), Maximum Spread (MS), and Spread of Non-Dominance Solution (SNS). Proposed solving methods for the studied problem and making comparisons between them are another innovation of this study. A couple of numerical examples are provided to illustrate the applicability of the presented solution methods. Finally, sensitivity analysis for problem parameters is performed to validate our suggested model. Our study reveals the superiority of the MOWOA over the other algorithms.

Multi-objective Mathematical Model for Optimal Wind Turbine Placement in Wind Farm under Uncertainty

The main objective of this research is to introduce three energy risk management models grounded in optimization techniques for the strategic placement of wind turbines, considering wake effects and uncertainties in wind speed and direction. For this purpose, wind speed and direction data are gathered, and Monte Carlo simulation is employed to model the uncertainties. Subsequently, the risk management models undergo optimization using Non-Dominated Sorting Genetic Algorithm II (NSGA-II), Pareto envelope-based selection algorithm II (PESA-II), and Multi-Objective Particle Swarm Optimization (MOPSO) algorithms. Findings reveal that the wind farm's maximum power output reaches approximately 5.8 megawatts across all three algorithms and optimal turbine placements. A risk assessment was conducted using a tenth percentile criterion, revealing a significant production risk within the study area, with production falling below 1.8 megawatts in 90% of cases. Regarding the performance evaluation of the algorithms across all three models, superior performance in terms of solution proximity to the ideal solution is exhibited by PESA-II, while enhanced diversity and solution spread compared to the other algorithms are demonstrated by NSGA-II.

Glycol Monomethyl Ether-Substituted Carbazolyl Hole-Transporting Material for Stable Inverted Perovskite Solar Cells with Efficiency of 25.52 .

Organic self-assembled molecules (OSAMs) based hole-transporting materials play a pivotal role in achieving highly efficient and stable inverted perovskite solar cells (IPSCs). However, the reported carbazol-based OSAMs have serious drawbacks, such as poor wettability for perovskite solution spreading due to the nonpolar surface, worse matched energy arrangement with perovskite, and limited molecular species, which greatly limit the device performance. To address above problems, a novel OSAM [4-(3,6-glycol monomethyl ether-9H-carbazol-9-yl) butyl]phosphonic acid (GM-4PACz) was synthesized as hole-transporting material by introducing glycol monomethyl ether (GM) side chains at carbazolyl unit. GM groups enhance the surface energy of Indium Tin Oxide (ITO)/SAM substrate to facilitate the nucleation and growth of up perovskite film, suppress cation defects, release the residual stress at SAM/perovskite interface, and evaluate energy level for matching with perovskite. Consequently, the GM-4PACz based IPSC achieves a champion PCE of 25.52 %, a respectable open-circuit voltage (VOC) of 1.21 V, a high stability, possessing 93.29 % and 91.75 % of their initial efficiency after aging in air for 2000 h or tracking at maximum power point for 1000 h, respectively.

Glycol Monomethyl Ether‐Substituted Carbazolyl Hole‐Transporting Material for Stable Inverted Perovskite Solar Cells with Efficiency of 25.52 %

AbstractOrganic self‐assembled molecules (OSAMs) based hole‐transporting materials play a pivotal role in achieving highly efficient and stable inverted perovskite solar cells (IPSCs). However, the reported carbazol‐based OSAMs have serious drawbacks, such as poor wettability for perovskite solution spreading due to the nonpolar surface, worse matched energy arrangement with perovskite, and limited molecular species, which greatly limit the device performance. To address above problems, a novel OSAM [4‐(3,6‐glycol monomethyl ether‐9H‐carbazol‐9‐yl) butyl]phosphonic acid (GM‐4PACz) was synthesized as hole‐transporting material by introducing glycol monomethyl ether (GM) side chains at carbazolyl unit. GM groups enhance the surface energy of Indium Tin Oxide (ITO)/SAM substrate to facilitate the nucleation and growth of up perovskite film, suppress cation defects, release the residual stress at SAM/perovskite interface, and evaluate energy level for matching with perovskite. Consequently, the GM‐4PACz based IPSC achieves a champion PCE of 25.52 %, a respectable open‐circuit voltage (VOC) of 1.21 V, a high stability, possessing 93.29 % and 91.75 % of their initial efficiency after aging in air for 2000 h or tracking at maximum power point for 1000 h, respectively.

Anomalies of solute transport in flow of shear-thinning fluids in heterogeneous porous media

Solute transport and mixing in heterogeneous porous media are important to many processes of practical applications. Most of the previous studies focused on solute transport in flow of Newtonian fluids, whereas there are many processes in which the phenomenon takes place in flow of a non-Newtonian fluid. In this paper, we develop a computational approach to evaluate and upscale dispersion of a solute in flow of a shear-thinning (ST) fluid in a heterogeneous porous medium. Our results indicate that the dispersivity is a non-monotonic function of the Péclet number and the shear rate, and this behavior is accentuated by the heterogeneity of the pore space and spatial correlations between the local permeabilities. As a result, solute transport in ST fluids deviates significantly from the same phenomenon in Newtonian fluids. Moreover, the shear-dependence of the dispersivity strongly influences the fate of solute transport in porous media at large length scales, including larger effluent concentration at the breakthrough point, which also occurs much faster than Newtonian fluids. To provide further evidence for the numerical findings, we compare dispersion in flow of a power-law fluid in a single tube with the same in a bundle of such tubes. Our results emphasize the shortcomings of the current theories of dispersion to account for the role of fluid rheology in solute mixing and spreading.

Unsteady solute dispersion of electro-osmotic flow of micropolar fluid in a rectangular microchannel

This study scrutinizes the two-dimensional concentration distribution for a solute cloud containing a micropolar fluid in a rectangular microchannel under the influence of an applied electric field. The concentration distribution is obtained up to second order approximation using Mei's homogenization method. Analytical formulas are derived for dispersion coefficient, mean and two-dimensional concentration distributions. This study also includes the analytical expressions for electric potential, velocity, and microrotation profiles. This study discusses the impact of coupling number, couple stress parameter, electric double layer thickness, and Péclet number on solute concentration distribution. The results of fluid velocity and dispersion coefficient are validated with available works in the literature. The non-Newtonian parameter and electric double layer thickness are shown to have a significant impact on dispersion. Our study reveals that concentration distribution rises but spreading of solute reduces when the coupling number increases. This is also true when the Debye length decreases. It is also obtained that the solute spreads more in the Newtonian fluid case compared to the micropolar fluid case. Finally, coupling number and electric double layer thickness show a symmetric pattern to the indicator function for the transverse concentration variation rate. The findings of this work have broad implications in deoxyribonucleic acid analysis, chemical mixing, and separation.

Ecological labour or why environmentally friendly practices struggle to become mainstream

This paper investigates the relationship between work and ecological transition by exploring ecological labour among neorurals, i.e., people who have left cities to live closer to nature in the countryside. In Diois, a mountainous area in south-eastern France where I did the fieldwork on which this paper is based, neorurals have been at the forefront of inventing more ecological ways of living for fifty years, but these solutions struggle to become mainstream. The article shows that under capitalism, ecological labour – defined as a human activity that goes into producing ecologically sustainable ways of living – struggles to become a job because it is labour-intensive and gets outcompeted by less ecological, technology-intensive alternatives. In contemporary France, ecological labour can become a “green job” only in the presence of superior purchasing power, otherwise it becomes unvalorised “reproductive” labour that limits the spread of ecological solutions. As long as the primary job-creation mechanism is built on two contradictory mechanisms – gains in labour productivity and strong local purchasing power – capitalist economies remain growth-addicted economies that upset ecosystems on an industrial scale.

Time-dependent dispersion coefficients for the evolution of displacement fronts in heterogeneous porous media

We present an approach for quantifying displacement fronts in heterogeneous porous media based on the concept of time-dependent apparent dispersion coefficients. The concept of constant asymptotic macrodispersion generally overestimates the area swept by a displacement front and leads to unrealistic upstream dispersion. We show that the large-scale front spreading can be captured by a one-dimensional advection–dispersion equation that is parameterized by a suitably chosen temporally evolving dispersion coefficient. For purely advective front spreading, we derive an analytical expression based on a predictive continuous time random walk approach, which applies to highly heterogeneous porous media. This analysis elucidates the variability of solute travel times as the key longitudinal spreading mechanism. It shows that the evolution of dispersion can be captured as the sum of exponentials that decay on two dominant time scales. In a particle-based picture, these scales mark the short time at which transported particles start exploring the flow variability and the large time at which the slowest particles start decorrelating their transport velocity. Based on these insights, we propose a heuristic formula that accounts for the impact of local-scale dispersion as an additional decorrelation mechanism. The heuristic expression for the longitudinal dispersion coefficient captures solute spreading for a broad range of Péclet numbers and heterogeneity variances. The proposed approach is tested against direct numerical simulations. It provides a robust and fast method for quantifying the evolution of displacement fronts in heterogeneous porous media with possible applications, for example, in groundwater contamination modelling, underground gas storage, and geothermal energy production.

Ganglionic Local Opioid Analgesia at the Superior Cervical Ganglion: MRI-Verified Solution Spread.

Ganglionic local opioid analgesia (GLOA) at the superior cervical ganglion (SCG) is performed for pain control and is known to be an effective procedure. In this study, we evaluated the spread of the injectate in the area of the SCG. Our expectation was that there would be a correlation between the area and volume of the injectate spread and post-procedural outcome measures. This was a retrospective blinded review of magnetic resonance imaging (MRI) scans. Assessors evaluated the anatomical area of fluid spread, the furthermost spread from midline, any hampered spread and contact of contrast fluid with other structures. The efficacy of GLOA and complications were estimated. The main solution spread reached from the C1 to C3 vertebrae. The furthest spread in the lateral and sagittal planes was 21.2 and 15.2mm, respectively. The furthest craniocaudal spread was 63.5mm. In 53.3% and 33% of interventions, the solution was found in the parapharyngeal space and in its "medial compartment," respectively. A correlation was found between pain relief and both solution spread and volume of solution spread. No hampered spread was recorded. A negative correlation between pain reduction and number of GLOA was observed. Higher pre-procedural pain intensity was correlated with higher pain reduction. We estimated pain relief in 93% of procedures correctly. No correlation between post-procedural Numerical Rating Scale (NRS) scores and different needle approaches was found. For the transoral blocking technique, a strict laterodorsal needle direction is recommended to prevent possible block failures. A total volume of 2ml injected into the parapharyngeal space and its "medial compartment" is recommended. Higher volumes may lead to uncontrolled distribution patterns. Clinicaltrials.gov identifier NCT05257655; date of registration 2022-02-25; patient enrollment date from 2023-01-09 to 2023-08-31.

Superspreading of Polyelectrolyte Complex Solution for Constructing Hydrogel Coatings on Diverse Substrates

AbstractInjectable hydrogels have emerged as versatile materials with potential applications in various fields, including biomedicine, lubrication, adhesion, surface coatings, and tissue engineering. However, the critical aspect of spreading and wetting on various substrates, which is essential for obtaining significant interfacial properties, has not been adequately addressed. This work presents an approach to prepare hydrogel coatings on kinds of substrates through the superspreading of polyelectrolyte complex solution during its liquid‐liquid phase inversion process. Due to the low interfacial tension, the solution spreads and wets various surfaces underwater driven by osmotic pressure, improving the contact area and interface integration. Combined with the simultaneous sol‐gel transition through electrostatic interaction, it forms a stable and homogeneous hydrogel coating. The hydrogel coating possesses control thickness (4–8 µm), improved hydrophilicity (CA decrease from 102° to 10°), interfacial toughness (increase from 70 to 455 J m−2), and lubrication performance (coefficients of friction decrease from 0.712 to 0.112). The work provides an excellent opportunity to investigate the spreadability and wettability in a water/water/solid three‐phase system and develop functional hydrogel coatings for various applications.

Incentive approaches for cloud computing: challenges and solutions

Cloud computing enables highly configurable and reliable computing resources on a rentable per-use scheme, facilitating quick and cost-effective provisioning of large-scale applications. Thanks to the fast-paced evolution of cutting-edge technologies and the rapid spread of cloud-based solutions, the cloud computing ecosystem is now part of our everyday lives. Nevertheless, cloud computing relies on highly sophisticated data centers comprising energy-consuming servers and equipment that require much energy. Stimulating cloud services for active participation and network contributions presents several challenges. Strategies based on artificial intelligence (AI), game theory, and blockchain have great potential to create an economically sustainable cloud ecosystem. This paper explores strategies grounded in AI, game theory, and blockchain to foster an economically sustainable cloud ecosystem. Informed by a survey study, our research delves into incentive approaches within cloud computing. Theoretical foundations, motivations, and enabling techniques are comprehensively examined to provide valuable insights for a broad audience. The primary contributions of this work lie in elucidating the application of AI, game theory, and blockchain to address challenges in incentivizing cloud services, paving the way for a more sustainable and efficient cloud computing landscape.

Uniform Nanoscale Ion-Selective Membrane Prepared by Precision Control of Solution Spreading and Evaporation.

Ion-selective membrane has broad application in various fields, while the present solution-processed techniques can only prepare uniform membrane with microscale thickness. Herein, a high-quality polymer membrane with nanoscale thickness and uniformity is precisely prepared by controlling solution spreading and solvent evaporation stability/rate. With the arrayed capillaries, the stable spreading of polymer solution with volume of microliter induces the formation of solution film with micrometers thickness. Moreover, the fast increase of solution dynamic viscosity during solvent evaporation inhibits nonuniform Marangoni flow and capillary flow in solution film. Consequently, the uniform Nafion-Li membranes with ∼200 nm thickness are prepared, while their Li+ conductivity is 2 orders of magnitude higher than that of commercially Nafion-117 membrane. Taking lithium-sulfur battery as a model device, the cells (capacities of 8-10 mAh cm-2) can stably operate for 150 cycles at a S loading of 12 mg cm-2 and an electrolyte/sulfur ratio of ∼7.

Widely distributable and retainable in-situ gelling material for treating myocardial infarction

Intramyocardial hydrogel injection is a promising therapy to prevent negative remodeling following myocardial infarction (MI). In this study, we report a mechanism for in-situ gel formation without external stimulation, resulting in an injectable and tissue-retainable hydrogel for MI treatment, and investigate its therapeutic outcomes. A liquid-like polymeric solution comprising poly(3-acrylamidophenylboronic acid-co-acrylamide) (BAAm), polyvinyl alcohol (PVA), and sorbitol (S) increases the viscous modulus by reducing the pre-added sorbitol concentration is developed. This solution achieves a sol-gel transition in-vitro in heart tissue by spontaneously diffusing the sorbitol. After intramyocardial injection, the BAAm/PVA/S with lower initial viscous modulus widely spreads in the myocardium and gelate compared to a viscoelastic alginate (ALG) hydrogel and is retained longer than the BAAm/S solution. Serial echocardiogram analyses prove that injecting the BAAm/PVA/S into the hearts of subacute MI rats significantly increases the fraction shortening and ejection shortening and attenuates the expansion of systolic LV diameter for up to 21 d after injection compared to the saline injection as a control, but the ALG injection does not. In addition, histological evaluation shows that only the BAAm/PVA/S decreases the infarct size and increases the wall thickness 21 d after injection. The BAAm/PVA/S intramyocardial injection is better at restraining systolic ventricular dilatation and cardiac failure in the rat MI model than in the control groups. Our findings highlight an effective injectable hydrogel therapy for MI by optimizing injectability-dependent distribution and retention of injected material. Statement of significanceIn-situ gelling material is a promising strategy for intramyocardial hydrogel injection therapy for myocardial infarction (MI). Since the sol-gel transition of reported materials is driven by external stimulation such as temperature, pH, or ultraviolet, their application in vivo remains challenging. In this study, we first reported a synthetic in-situ gelling material (BAAm/PVA/S) whose gelation is stimulated by spontaneously reducing pre-added sorbitol after contacting the heart tissue. The BAAm/PVA/S solution spreads evenly, and is retained for at least 21 d in the heart tissue. Our study demonstrated that intramyocardial injection of the BAAm/PVA/S with more extensive distribution and longer retention had better effects on preventing LV dilation and improving cardiac function after MI than that of viscoelastic ALG and saline solution. We expect that these findings provide fundamental information for the optimum design of injectable biomaterials for treating MI.

Midpoint Transverse Process to Pleura Block for Postoperative Analgesia in Laparoscopic Cholecystectomy: A Pilot Study and Review of Literature

Abstract Background: Midpoint transverse process to pleura block (MTPB) provides a close anatomical alternative to paravertebral block (PVB). The extent of the drug spread in MTPB and analgesic equivalence of MTPB with PVB and other “paravertebral by proxy” blocks are still under study. Methodology: Ten patients posted for elective laparoscopic cholecystectomy were administered general anesthesia, followed by bilateral ultrasound-guided MTPBs. A total of 20 mL of the drug mixed with iohexol dye solution was injected in each block. Postoperative pain scores were assessed. The spread of drug dye solution under ultrasound and fluoroscopy was studied. Results: Eighty percent of patients had NRS < 3 in the postanesthesia care unit. “Pain score” at 24 h was 2 for three patients and 1 for all other patients. The dye spread under fluoroscopy was observed to extend up to 5–7 levels of cephalad and 5–6 levels of caudad from the point of injection. Sonographic drug spread in the paravertebral space was visualized in 13 out of 20 (65%) blocks. Conclusion: With the results of our study and review of literature, it reflects that MTPB is an effective analgesic adjunct in thoracic surgeries and appears promising in abdominal surgeries as well. In laparoscopic cholecystectomies, its potential role in reducing shoulder pain should be explored further. Currently, it is not possible to recommend MTPB over PVB or erector spinae plane block (ESPB). Yet, it is to acknowledge the presence of the “midpoint transverse process to pleura” area as a definite injection target, which may confer some advantages over PVB and ESPB.

Research of the movement of solutions in waterless dry horizons

The movement of solutions in waterless dry layers and the influence of irrigated rock on the radius the filtration flow and the nature of its saturation were established in the paper. The liquid flow curves were constructed for various distances from the source axis. The developed methodology of non-stationary filtration mode during underground leaching determined the filtration coefficients in laminar and turbulent modes. It is necessary to take into account the physical properties of both the rock mass and the filtered leaching solutions. Research has established that the shape of the spreading of solutions in the system of interaction between the injection and discharge wells (the edge boundaries of the streamline) must be considered as a rhombus, and the spreading angle is formed depending on the degree of clogging of the pore volume.

Study on Marangoni explosion of binary mixtures in liquid layer

In this work, the process of forming micro-droplets due to instability and fragmentation after short chain alcohol solution spreads on the surface of oil layers is studied. Based on the free energy theory of the liquid-liquid interface, the relationship between the binary mixtures spreading on the surface of the liquid layer is derived, and the concentration range of short chain alcohol solution spreading as a thin film on the surface of the oil layer is calculated from the Hiskovsky formula. The Malangoni flow caused by the difference in evaporation rate between the center and edge of the droplet film perturbs the boundary of the liquid film, causing finger-shaped liquid columns to grow at the edge when the droplet spreads to its maximum. In this work, the expression for the critical wavelength and maximum wavelength of boundary instability are derived based on the perturbation model, and the reason for finger shaped liquid column fragmentation is explained based on the Plateau Rayleigh instability. A concentric cylindrical shell liquid column model is established to simplify the calculation and predict the location range of “droplet explosion” of droplets with different viscosity ratios on the liquid layer. Through theoretical calculations and experimental verification, it is found that the alcohol solution fragmented into small droplets within a length range of 4.51–5.98 times the width of the liquid column. This study provides theoretical guidance for existing application fields such as film forming technology and coating technology. The hypotheses, assumptions, and simplified models preliminarily verified experimentally provide solutions for some technical difficulties in the research fields of micro reactions and nanoparticle preparation in chemical industry.

Multi-objective dragonfly algorithm for optimizing a sustainable supply chain under resource sharing conditions

This research addresses optimizing production, inventory, location, and routing in a multi-level supply chain. In the studied supply chain, products are first sent to several distribution centers (DC) after production. Next, these products are delivered to several companies. Companies are divided into two independent groups considering sharing logistics resources. In this regard, vehicle routing optimization is applied for each group. For this purpose, a mixed-integer linear programming model has been developed. This model simultaneously minimizes total supply chain costs and total negative environmental impacts. A multi-objective dragonfly algorithm (MODA) has been developed to solve this model. Then, the implementation results are compared with the Non-Dominated Sorting Genetic Algorithm and Epsilon Constraint Method (EPC). Comparing the solution methods based on numerous test problems shows that the proposed MODA algorithm can be examined differently. The MODA algorithm has been able to have a significant advantage in providing solutions close to ideal points. Moreover, this algorithm has provided the most effective Pareto solutions in different test problems. However, the NSGA-II algorithm performs better regarding the spread of non-dominated solutions.

Dynamic rainfall-induced landslide susceptibility: A step towards a unified forecasting system

The initial inception of the landslide susceptibility concept defined it as a static property of the landscape, explaining the proneness of certain locations to generate slope failures. Since the spread of data-driven probabilistic solutions though, the original susceptibility definition has been challenged to incorporate dynamic elements that would lead the occurrence probability to change both in space and in time. This is the starting point of this work, which combines the traditional strengths of the susceptibility framework together with the strengths typical of landslide early warning systems. Specifically, we model landslide occurrences in the norther sector of Vietnam, using a multi-temporal landslide inventory recently released by NASA. A set of static (terrain) and dynamic (cumulated rainfall) covariates are selected to explain the landslide presence/absence distribution via a Bayesian version of a binomial Generalized Additive Models (GAM). Thanks to the large spatiotemporal domain under consideration, we include a large suite of cross-validation routines, testing the landslide prediction through random sampling, as well as through stratified spatial and temporal sampling. We even extend the model test towards regions far away from the study site, to be used as external validation datasets. The overall performance appears to be quite high, with Area Under the Curve (AUC) values in the range of excellent model results, and very few localized exceptions.This model structure may serve as the basis for a new generation of early warning systems. However, the use of The Climate Hazards group Infrared Precipitation with Stations (CHIRPS) for the rainfall component limits the model ability in terms of future prediction. Therefore, we envision subsequent development to take this direction and move towards a unified dynamic landslide forecast. Ultimately, as a proof-of-concept, we have also implemented a potential early warning system in Google Earth Engine.