Subsequent Process Research Articles

Investigation of frontier Multi-Armed Bandit algorithms and applications

Since the amount of content online is growing exponentially and people's time is limited, there is an urgent need for a high-performance algorithm that can make effective recommendations. This paper will introduce a recommendation system model, a sequential decision model, which is called Multi-Armed Bandit. The main idea of the Multi-Armed Bandit model is that at the beginning of the algorithm, all the recommended items are set to the same weight. In the subsequent recommendation process, the model explores the distribution of each item while changing the weight of each item according to the average revenue of each item, and selects more items with larger weight. This paper will introduce three cutting-edge Multi-Armed Bandit algorithms, their algorithmic ideas and their respective characteristics. The idea of Explore-Then-Commit (ETC) algorithm is to explore each item a certain number of times, and then select the best item for subsequent recommendation. The idea of the Upper Confidence Bound (UCB) algorithm is to represent the "exploration" and "exploitation" of each item by numerical values and add them to the UCB value, and select the item with the largest UCB value each time. The idea of TS is to first assume the distribution of each item, and then change the parameters of the distribution of each item based on the reward. At the end, this paper will introduce several scenarios where Multi-Armed Bandit algorithms can be used to give the reader an idea of how to use Multi-Armed Bandit algorithms.

A Study on the Influence of Drying and Preheating Parameters on the Roasting Properties of Limonite Pellets

In this experiment, a pellet preparation method was investigated to study the drying, preheating, and roasting properties of limonitic iron ore from a plant in Yunnan. The aim was to improve the subsequent iron-making process of limonitic iron ore and make it a substitute for sintered ore. This substitution would reduce the amount of blast furnace slag in the iron-making process. Bentonite is commonly used as a primary binder in many pelletizing plant operations. However, its excessive usage leads to a higher risk of slagging and coking in the furnace. In this paper, we aim to decrease the quantity of bentonite added, enhance the iron content in the pellets, and reduce impurities to improve the grade of limonite pellets. The results show that the optimal drying, preheating, and roasting temperatures of limonite pellets are 200 °C, 700 °C, and 1250 °C, respectively, and the optimal roasting time is 20 min, when the diameter of the pellets is 8–13 mm. The compressive strength of limonite pellets with the addition of 1.5% bentonite was the highest, meeting the demands of a general blast furnace, based on which the iron grade of limonite pellet ore was increased by 10.63%.

Valorization of refinery flue gas through tri‐reforming and direct hydrogenation routes

AbstractThe rising amount of greenhouse gases has been contributing to global warming and, subsequently, climate change. Industries such as refineries and power plants emit a significant amount of CO2 into the atmosphere. It is imperative to curb anthropogenic CO2 emissions, and hence, in this effort, we explore the utilization of a refinery emission stream to produce value‐added chemicals. The chosen emission stream for the said purpose is a typical flue gas stream from refineries. Following the capture step, this CO2 stream has been leveraged for subsequent valorization processes. Two strategies have been proposed in this paper to valorize the captured carbon dioxide. The first strategy employs the tri‐reforming process with a refinery‐specific fuel gas stream as the co‐reactant. The resulting syngas from tri‐reforming has been converted to chemicals such as methanol (MET) and ethanol. Furthermore, to improve the amount of CO2 valorized, another approach with green hydrogen has been considered. The second strategy aims at direct hydrogenation of the captured CO2 stream to produce MET and ethanol. The proposed strategies analyze the feasibility of valorizing captured CO2 from flue gas to MET and ethanol in terms of gross margin per feed and percentage of CO2 valorization. The performance assessment and analysis of the proposed processes have been carried out using simulations in Aspen Plus® that exhibited up to 74% valorization of CO2 into valuable chemicals.

Real time object tracking using deep learning and OpenCV

This article summarizes the background and application fields of Open-Source Computer Vision Library (OpenCV) and deep learning and conducts research based on their object detection and tracking applications. The model algorithm selected in this article is the Convolutional Neural Networks (CNN) algorithm. CNN algorithm can be used for object detection in real-time scenarios. Moreover, the CNN algorithm has good credibility. The Python program developed based on CNN algorithm can effectively achieve real-time object tracking. The model shows good detection and tracking performance for trained targets and can be further applied in more specific scenarios in the future. Because deep learning can process large-scale data and recognize complex patterns, it can automatically learn and extract advanced features. Combining the two can achieve faster and more accurate detection and tracking of target objects. After having a large enough training sample size, it can detect and track the specified object more accurately. However, it is precisely due to the enormous sample size required for deep learning that there are still some difficulties in applying it to real-time object tracking. This article first discusses the use of supervised learning methods for deep understanding. When the input sample capacity is large enough, the machine can better reflect the real-time detection and tracking of the target object. But the time required will significantly increase. This issue still needs to be addressed in the subsequent research process.

Janus Kinase Inhibitor Brepocitinib Rescues Myelin Phagocytosis Under Inflammatory Conditions: In Vitro Evidence from Microglia and Macrophage Cell Lines.

Central nervous system (CNS) injuries induce cell death and consequently the release of myelin and other cellular debris. Microglia as well as hematogenous macrophages actively collaborate to phagocyte them and undergo their degradation. However, myelin accumulation persists in the lesion site long after the injury with detrimental effects on axonal regeneration. This might be due to the presence of inhibitors of phagocytosis in the injury site. As we recently published that some proinflammatory stimuli, like interferon-γ (IFNγ) and lipopolysaccharide (LPS), inhibit myelin phagocytosis in macrophages, we have now studied the signaling pathways involved. A phagocytosis assay in Raw264.7 macrophages and N13 microglia cell lines with labeled myelin was developed with the pHrodo reagent that emits fluorescence in acidic cellular compartments (e.g.lysosomes). Pharmacological inhibition of Janus kinases (Jak) with Brepocitinib restored myelin phagocytosis and rescued the expression of genes related to phagocytosis, like triggering receptor expressed on myeloid cells 2 (TREM2), induced by IFNγ or LPS. In addition, while pharmacological inhibition of the signal transducer and activator of transcription 3 (STAT3) rescued myelin phagocytosis and the expression of phagocytosis related genes in the presence of LPS, it did not have any effect on IFNγ-treated cells. Our results show that Jak pathways participate in the inhibition of myelin phagocytosis by IFNγ and LPS. They also indicate that the resolution of inflammation is important for the clearance of cellular debris by macrophages and subsequent regenerative processes.

Gravity-based pre-concentration strategies for complex rare earth ore containing niobium and zirconium

The Balzhe rare earth mine, renowned for its rich reservoirs of niobium, zirconium, and rare earth elements, poses a unique challenge due to its diverse and interbedded mineral composition. Despite the abundance of these elements, their valuable grade remains notably low, falling short of economic thresholds. To this end, pre-concentration of valuable minerals to discard gangue minerals before flotation would be an economical option. In response, this study delves into the feasibility of gravity-induced pre-concentration, aiming to segregate valuable minerals from gangue for subsequent flotation processes. Conducting float-and-sink tests on varied particle sizes (-2+0.5 mm, -0.5+0.074 mm, and -0.074+0.02 mm) within heavy liquids of specific gravities (ranging from 2.55 to 2.85), the study reveals the effectiveness of gravity separation. Notably, particles sized -2+0.5 mm and -0.074+0.02 mm demonstrated superior separation performance over the -0.5+0.074 mm fraction. Comparative analysis of diverse gravity separation equipment unveiled compelling results. The dense medium cyclone separator showcased impressive recovery rates and high-grade concentrates of Nb<sub>2</sub>O<sub>5</sub>, ZrO<sub>2</sub>, and total rare earth oxides (TREO) at 0.34%, 8.20%, and 0.41%, respectively, surpassing the sand table's performance for -2+0.5 mm particles. Conversely, for -0.5+0.074 mm particles, the shaking table exhibited optimal separation efficiency, yielding grades of Nb<sub>2</sub>O<sub>5</sub>, ZrO<sub>2</sub>, and TREO at 0.37%, 4.08%, and 0.44%, with substantial recovery values. Ultimately, the Knelson centrifugal separator proved most effective for -0.074+0.02 mm particles, yielding notable grades and recoveries of Nb<sub>2</sub>O<sub>5</sub>, ZrO<sub>2</sub>, and TREO. This study underscores the promising potential of gravity-induced pre-concentration techniques for enhancing the recovery of valuable elements from the complex Balzhe rare earth ore, offering critical insights into optimizing mineral extraction processes.

Dual-input ultralight multi-head self-attention learning network for hyperspectral image classification

ABSTRACT In the hyperspectral image (HSI) classification tasks, various deep learning models have achieved remarkable success. However, most deep learning models are compute-intensive, requiring significant computing power, time, and other resources. It becomes a challenge to pursue better results while saving computational resources. Therefore, a novel dual-input ultralight multi-head self-attention learning network (DUMS-LN) is proposed for HSI classification. The proposed DUMS-LN consists of three main core modules, namely the high-dimensional reduced module (HDRM), lightweight multi-head self-attention (LMHSA) module, and linearized hierarchical conversion module (LHCM). HDRM is used as a pre-processing module with efficient data compression and combines spatial and spectral information extraction from the raw data to provide cleaner and more comprehensive feature data for subsequent processing. In addition, the core computational module of DUMS-LN is the LMHSA module, which is lightweight but possesses better data processing capability than the traditional multi-head self-attention module. Finally, the LHCM divides the model into two phases, reducing the dimensionality of the feature data phase by phase so that the LMHSA module can perform feature extraction at different levels. Experiments on four benchmark HSI datasets show that the proposed DUMS-LN outperforms the comparison HSI classification algorithms regarding speed and classification accuracy.

Mobility from the Catholic Religion to the “without Religion” Identification in Young University Students in Chile

In recent years, Chile has experienced a highly significant abandonment of the Catholic church. This can be observed in young people, who have left its organizational spaces and their identification with it. The magnitude of this growing abandonment, which has been heighted by the public awareness of sexual abuse committed by priests, has been shown in quantitative studies, however, they do not delve into the reasons of those who distance themselves from the church. This article presents research results that identify the motivations expressed by young people that led them to stop being Catholic and places this phenomenon of disaffection within a bigger issue that has been occurring for some time: that of a religious mobility in an increasingly secular society, where the number of people who identify themselves as “without religion” continues to grow. By means of individual interviews, the reasons given by young people were identified and later validated in a subsequent group interview process.

Flexi-EIT: A Flexible and Reconfigurable Active Electrode Electrical Impedance Tomography System.

Electrical Impedance Tomography (EIT) systems have shown great promise in many fields such as real-time wearable healthcare imaging, but their fixed number of electrodes and placement locations limit the system's flexibility and adaptability for further advancement. In this article, we propose a flexible and reconfigurable EIT system (Flexi-EIT) based on digital active electrode (DAE) architecture to address these limitations. By integrating a reconfigurable number of up to 32 replaceable DAEs into the flexible printed circuit (FPC) based wearable electrode belt, we can enable rapid, reliable, and easy placement while maintaining high device flexibility and reliability. We also explore hardware-software co-optimization image reconstruction solutions to balance the size and accuracy of the model, the power consumption, and the real-time latency. Each DAE is designed using commercial chips and fabricated on a printed circuit board (PCB) measuring 13.1 mm × 24.4 mm and weighing 2 grams. In current excitation mode, it can provide programmable sinusoidal current signal output with frequencies up to 100 kHz and amplitudes up to 1 mA p-p that meets IEC 60601-1 standard. In voltage acquisition mode, it can pre-amplify, filter, and digitize the external response voltage signal, improving the robustness of the system while avoiding the need for subsequent analog signal processing circuits. Measured results on a mesh phantom demonstrate that the Flexi-EIT system can be easily configured with different numbers of DAEs and scan patterns to provide EIT measurement frames at 38 fps and real-time EIT images with at least 5 fps, showing the potential to be deployed in a variety of application scenarios and providing the optimal balance of system performance and hardware resource usage solutions.

A superior sodium-ion anode material from PAN/lignin-derived carbon nanofibers with inter-connected structure prepared through phosphoric acid induced cross-linking

A feasible route to fabricate phosphorus-doped carbon nanofibers (P-CNFs) with an inter-connected structure has been demonstrated through electrospinning, stabilization, and subsequent phosphoric acid impregnation and carbonization processes using polyacrylonitrile and lignin as carbon sources. The results illustrate that the phosphoric acid induced cross-linking could be beneficial to acquire the closed-pore structure and the heteroatom-doped surface chemistry of nanofibers. As a result, the P-CNFs exhibit higher interlayer spacing of graphite and lower BET specific surface area compared to the pristine CNFs. The P-CNFs as an anode material for sodium-ion batteries (SIBs) present a high reversible capacity 278 mA h g−1 at 0.2 A g−1 and a superior initial Coulomb efficiency (ICE) of 78.86 %. Moreover, the reversible capacity of P-CNFs can be stably maintained near the initial capacity after 5000 cycles at 1 A g−1, showing exceptional structural stability and cycling durability. Meanwhile, the sodium storage mechanism of P-CNFs was investigated using in-situ Raman and ex-situ XRD analysis to understand the exceptional structural stability and Na+ adsorption capacity of P-CNFs. This work provides valuable insights for the design of carbon nanofibers with an inter-connected structure as anode materials for SIBs, exhibiting outstanding electrochemical properties.

Review of atomization characteristics of liquid jets in crossflow

The atomization process of liquid fuels is vital in scramjet engines. The level of atomization directly impacts the subsequent evaporation, mixing, and combustion processes. Therefore, understanding the atomization mechanism of liquid jets in crossflow is necessary to promote the mixing process of scramjet engines and improve the combustion efficiency. This article overviews the atomization process of liquid jets in transverse airflow based on the breakup mechanism, atomization characteristics, and factors affecting atomization. The deformation and fragmentation of droplets are influenced primarily by the Weber number and have little correlation with the Reynolds number. There are similarities in the properties between the primary fragmentation of liquid jets and the breakup of liquid droplets in crossflow. The primary breakup of liquid jets in crossflow is characterized primarily by continuous jet column breakup. The Rayleigh–Taylor instability causes columnar breakup, while the Kelvin–Helmholtz instability causes surface breakup in the jet. The size distribution of droplets follows C-, I-, or S-shaped distributions, while the velocity distribution of droplets follows an inverse C-shape. Finally, the shortcomings of current research are pointed out, namely, the lack of research on the jet breakup mechanism in crossflow under actual scramjet engine configurations and inflow conditions. In the future, it can be combined with artificial intelligence to reveal the jet breakup mechanism under actual working conditions and establish a wide range of theoretical prediction models.

The Role of Ultrasonography in Diagnosing and Managing Sialolithiasis: A Case Report and Literature Review

Abstract Sialolith-induced obstructive sialadenitis is a commonly encountered clinical scenario, yet the variations in the size and location of the stone can complicate immediate clinical assessment. Utilizing dynamic ultrasound imaging along with specific structural markers can provide valuable, immediate objective evidence in diagnosing submandibular sialolithiasis. This initial ultrasound evaluation streamlines the decision-making process by facilitating the timely scheduling of confirmatory computed tomography scans and guiding subsequent surgical interventions. This case report illustrates how in-office ultrasonography expedited the diagnosis and subsequent surgical decision-making process for submandibular sialolithiasis within a span of just 1 week.

Cobot selection using hybrid AHP-TOPSIS based multi-criteria decision making technique for fuel filter assembly process

The choice of a suitable collaborative robot (cobot) for a real-time industrial process is one of the obstacles to effective robot implementation in terms of energy and cost. The cobot selection process for an application have become more complex due to increasing sophisticated features and capabilities in cobots offered by the manufacturers. The paper presents a hybrid Multi-Criteria Decision-Making (MCDM) technique based on Analytical Hierarchy Process (AHP) and Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) approaches for selecting cobots for fuel filter assembly operation. The product design methodology, manufacturing method, and associated cost are directly influencing the decision on cobot selection. The most appropriate robot to accomplish the desired task at the lowest possible cost and capability can be selected by AHP with prospective criterion weight for subsequent processing. The TOPSIS approach orders alternatives based on the prominence of criteria. A diesel fuel filter assembly process case was considered for validating the proposed technique of cobot selection process. An expert knowledge base was generated for 12 advocated cobots and the best cobot was selected using the proposed hybrid MCDM technique.

Electroosmosis of viscoelastic fluids in pH-sensitive hydrophobic microchannels: Effect of surface charge-dependent slip length

We analytically investigated the electroosmotic flow characteristics of complex viscoelastic liquids within a charged hydrophobic microchannel, considering the pH and salt concentration-dependent surface charge effects in our analysis. We examined the variation of the electric-double layer (EDL) potential field, the surface charge-dependent slip (SCDS) length, the flow field, the viscosity ratio, and both normal and shear stresses in relation to the bulk pH, bulk salt concentration, and Deborah number of the solution. Our current findings indicate that, under strong flow resistance due to increased electrical attraction on counter ions, a highly basic solution with a high EDL potential magnitude results in a significant decrease in the slip length. Neglecting the effect of SCDS leads to an overestimation of flow velocity, with this overprediction being more pronounced for highly basic solutions. This overestimation diminishes as bulk salt concentration increases, particularly when compared to strongly acidic solutions. Furthermore, a noticeable increase in average velocity is observed as the Deborah number rises for highly basic solutions compared to highly acidic ones. This is attributed to the substantial reduction in apparent viscosity caused by the shear-thinning nature of the liquid at higher shear rates, supported by a larger zeta potential modulated strong electrical force for basic solutions. Additionally, we found that the intensity of shear and normal stresses tends to increase with bulk pH, primarily due to the rise in electric body force at higher zeta potential. These results can potentially inform the design and development of a compact, nonmoving electroosmotic pump for transporting biological species with varying physiological properties, such as solution pH. This technology could be applied in subsequent processes involving mixing, separation, flow-focusing for cell sorting, and other related applications.

Recycling of deep eutectic solvent in the extraction of ferulic acid from oil palm empty fruit bunch.

The study explored ferulic acid extraction from palm empty fruit bunch (EFB) fiber using deep eutectic solvent (DES) of chlorine chloride-acetic acid as the extraction medium and the way to recover and recycle the DES thereafter. Antisolvent was added to selectively precipitate the ferulic acid, which was recovered by filtration thereafter. Recycling the DES without further purification led to increased ferulic acid yield with each subsequent extraction, likely due to retained ferulic acid. The retained ferulic acid and other impurities could be removed by precipitation brought upon by the addition of a second antisolvent. 1H nuclear magnetic resonance revealed that there was no excess ferulic acid in the recycled DES-treated with two types of antisolvents (ethanol and water). The yield of ferulic acid increased from 0.1367-0.1856g/g when treated with only one antisolvent to 0.1368-0.2897g/g with two antisolvent treatments. Oil droplets were also observed in the DES upon the addition of antisolvent 2, with recovered oil ranging from 0.6% to 3%. The study emphasized the significance of using DES as an extraction medium for ferulic acid from oil palm EFB fiber and the method to recycle the DES for subsequent processes.

Clean and efficient synthesis of LiFePO4 cathode material using titanium white waste and calcium dihydrogen phosphate

Large amounts of titanium white waste are generated in the production of titanium dioxide using sulphate method, which in turn can be used to prepare LiFePO4 cathode material, thereby reducing environmental risks and achieving resource recovery. However, a key challenge lies in the elimination of impurities. In this work, a cost-efficient and straightforward approach based on phase transformation during hydrothermal treatment was proposed to utilize titanium white waste with calcium dihydrogen phosphate for the preparation of LiFePO4 cathode material. The content of Fe in the leachate was enriched to 81.5 g/L after purification, while 99.9% of Ti and 98.36% of Al and were successfully removed. In the subsequent process for Fe/P mother liquor preparation, the losses of Fe and P were only 5.82% and 2.81%, respectively. The Fe and P contents of the synthesized FePO4 product were 29.47% and 17.08%, respectively, and the Fe/P molar ratio was 0.986. Crystal phase of the product matched well with standard iron phosphate, and the lamellar microstructure of FePO4 was uniform with the particle size ranging from 3 to 5 μm. Moreover, the contents of impurities in the product were far below the standard. The initial discharge of LiFePO4 synthesized by the iron phosphate was 160.6 mAh.g-1 at 0.1 C and maintained good reversible capacity after 100 cycles. This work may provide new strategy for preparing LiFePO4 cathode material from industrial solid waste.

Photolysis of Dissolved Organic Matter over Hematite Nanoplatelets.

Solar photoexcitation of chromophoric groups in dissolved organic matter (DOM), when coupled to photoreduction of ubiquitous Fe(III)-oxide nanoparticles, can significantly accelerate DOM degradation in near-surface terrestrial systems, but the mechanisms of these reactions remain elusive. We examined the photolysis of chromophoric soil DOM coated onto hematite nanoplatelets featuring (001) exposed facets using a combination of molecular spectroscopies and density functional theory (DFT) computations. Reactive oxygen species (ROS) probed by electron paramagnetic resonance (EPR) spectroscopy revealed that both singlet oxygen and superoxide are the predominant ROS responsible for DOM degradation. DFT calculations confirmed that Fe(II) on the hematite (001) surface, created by interfacial electron transfer from photoexcited chromophores in DOM, can reduce dioxygen molecules to superoxide radicals (•O2-) through a one-electron transfer process. 1H nuclear magnetic resonance (NMR) and electrospray ionization Fourier-transform ion cyclotron resonance mass spectrometry (ESI-FTICR-MS) spectroscopies show that the association of DOM with hematite enhances the cleavage of aromatic groups during photodegradation. The findings point to a pivotal role for organic matter at the interface that guides specific ROS generation and the subsequent photodegradation process, as well as the prospect of using ROS signatures as a forensic tool to help interpret more complicated field-relevant systems.

Perceptions of Stakeholders on the Financial and Economic Crisis in Lebanon: an in-Depth Analysis

Purpose: The objective of this study is to delve into the root causes of Lebanon's severe economic crisis. This crisis has been exacerbated by a confluence of factors, including the impact of the COVID-19 pandemic, pre-existing economic difficulties, and the devastating Beirut explosion. The aim is to uncover the fundamental drivers behind the crisis, which encompass issues such as financial mismanagement, governmental shortcomings, excessive debt burdens, intricate financial engineering practices, and political unrest. Methodology: Employing a quantitative methodology, this research leverages a survey of 178 pertinent stakeholders. The approach encompasses both descriptive analysis and factor analysis. Descriptive statistics were calculated for each variable, providing a comprehensive overview of the perspectives held by the participants. This initial step then guided the subsequent process of factor analysis, which was executed utilizing Principal Component Analysis (PCA) as the technique. Findings: The results disclose a complex array of factors that have collectively contributed to the current economic turmoil in Lebanon. The presence of a dominant underlying component indicates a strong association between variables related to financial mismanagement, government failures, public debt, financial engineering techniques, and political instability. These factors play a substantial role in driving the crisis, indicating an intricate web of interrelated elements contributing to the country's financial downturn. Research Limitations/Implications: While this study provides valuable insights into the origins of the crisis, it is important to acknowledge certain limitations. The research primarily relies on quantitative data and stakeholder surveys, which may not capture the entirety of the complex socio-political and economic dynamics at play. Additionally, the study does not delve deeply into potential geopolitical factors that may also be influencing the crisis. Originality/Value: This research contributes to the existing body of knowledge by offering a data-backed analysis of the Lebanon economic crisis. The identification of specific drivers such as financial mismanagement, governmental failures, and political unrest provides a foundation for targeted policy recommendations. The study emphasizes the importance of implementing prudent fiscal practices, governance reforms, and tailored policies to address the crisis and prevent similar situations in the future.

Mechanical and environmental evaluation of PET plastic-graphene nano platelets concrete mixes for sustainable construction

In recent times, there has been a substantial increase in the annual use of plastics, resulting in a major upward trend. As a result, recycling plastic waste has become a major global issue. The present research aims to explore the feasibility of utilizing Polyethylene terephthalate (PET) as a possible substitute for coarse aggregate in concrete. In addition, the integration of Graphene Nano-platelets (GNPs) into the concrete mixture was conducted using different quantities, aiming to improve its structural integrity. The study employed an experimental research design to carry out its examination. PET was included into concrete at varied ratios, namely 0 %, 5 %, 15 %, 20 %, and 25 %, serving as an additional ingredient alongside coarse aggregate. Additionally, GNPs were introduced into the mixture at various weight percentages, namely 0 %, 0.03 %, 0.05 %, 0.08 %, and 0.1 %. A series of mechanical tests were performed to evaluate various properties of the concrete, including compressive strength (CS), split tensile strength (STS), flexural strength (FS), modulus of elasticity (MoE), ultrasonic pulse velocity (UPV). In addition, an assessment of the concrete's environmental impact was conducted by analysing the carbon content and evaluating its eco-efficiency (ESE). The research study revealed that the incorporation of 5 % PET as a replacement for coarse aggregate, together with the inclusion of 0.1 % GNPs, resulted in the optimal enhancement of CS, STS, FS, MOE, UPV by 9 %, 12.21 %, 4.40 %, 4.40 % and 0.070 % respectively. The Response Surface Methodology (RSM) models were developed, and mathematical equations were generated in order to predict the expected results. The optimization process for all the models was carried out using a multi-objective optimization technique, followed by a subsequent validation process.

Bioactive nanomaterials kickstart early repair processes and potentiate temporally modulated healing of healthy and diabetic wounds

Slow-healing and chronic wounds represent a major global economic and medical burden, and there is significant unmet need for novel therapies which act to both accelerate wound closure and enhance biomechanical recovery of the skin. Here, we report a new approach in which bioactives that augment early stages of wound healing can kickstart and engender effective wound closure in healthy and diabetic, obese animals, and set the stage for subsequent tissue repair processes. We demonstrate that a nanomaterial dressing made of silk fibroin and gold nanorods (GNR) stimulates a pro-neutrophilic, innate immune, and controlled inflammatory wound transcriptomic response. Further, Silk-GNR, lasered into the wound bed, in combination with exogeneous histamine, accelerates early-stage processes in tissue repair leading to effective wound closure. Silk-GNR and histamine enhanced biomechanical recovery of skin, increased transient neoangiogenesis, myofibroblast activation, epithelial-to-mesenchymal transition (EMT) of keratinocytes and a pro-resolving neutrophilic immune response, which are hitherto unknown activities for these bioactives. Predictive and temporally coordinated delivery of growth factor nanoparticles that modulate later stages of tissue repair further accelerated wound closure in healthy and diabetic, obese animals. Our approach of kickstarting healing by delivering the “right bioactive at the right time” stimulates a multifactorial, pro-reparative response by augmenting endogenous healing and immunoregulatory mechanisms and highlights new targets to promote tissue repair.