Manufacturing Procedure Research Articles

Application of Polydopamine-Based Magnetic Solid-Phase Extraction for Highly Sensitive Determination of Aristolochic Acid I from Traditional Chinese Medicine Samples.

A low cost-effective and simple synthesis method combining magnetic solid-phase extraction (MSPE) and high-pressure liquid chromatography was developed for the analysis of aristolochic acids I (AAI) in traditional Chinese medicine samples. A novel polydopamine (PDA) modified magnetic nanoparticles with one single carbon layer (Fe3O4@1C NPs) via one-pot hydrothermal approach was prepared and then successfully employed to extract AAI for the first time. Dopamine (DA) can form a PDA layer on Fe3O4@1C NPs surface through self-polymerization to form Fe3O4@1C@PDA. As a surface modifier of DA, PDA offered more adsorption sites to AAI due to π-π stacking, hydrogen bonding and electrostatic interactions. The parameters of MSPE were optimized by univariate and multivariate methods (Box-Behnken design) in detail. High degree of linearity was obtained in the range of 0.05-200.0μg/mL. The limits of detection (S/N = 3) and quantification (S/N = 10) were 0.08 and 0.25μg/mL, respectively. The recoveries of AAI in spiked Xiaoqinglong mixture samples were in the range of 86.7 to 108.5% with the relative standard deviation of less than 5.2%. Thus, a fast, convenient, sensitive and eco-friendly method was successfully proposed and became a promising approach for the determination of AAI in herbal plants or its preparation in the manufacturing procedure.

Optimized YOLOv8 based on SGW for surface defect detection of silicon wafer

Abstract Wafer detection is a critical procedure in IC manufacturing. Deep learning models are extensively used to identify the wafer defects. The key issue is how to recognize the small defects in complex backgrounds reducing the probability of misjudge and enhancing the detection accuracy. To solve the problems, we proposed a new detection model, SGW-YOLOv8 (SimAM-GhostConv-Wise IOU), based on the YOLOv8 model. The SimAM attention mechanism was added to enhance the network's focus on important positions without increase of the parameter numbers. The GhostConv improved the backbone network, and the Wise-IOU (Weighted Intersection over Union) loss function was introduced to address the deviation of evaluation results caused by the traditional loss function. Moreover, an additional detection head was appended to YOLOv8 to improve the model's capability of recognizing small targets. The dataset containing six types of defects was established by generating 6000 images of silicon wafers. The experimental results demonstrated that the mAP@0.5 of SGW-YOLOv8 increased by 4.8% compared to YOLOv8, and the model parameters are decreased by 11.8%. Therefore, the proposed SGW-YOLOv8 model is potential for wafer detection in IC industry.

A revolutionary approach to automate labelling of CAD files

Abstract This innovation represents a significant advancement in enhancing processing efficiency when dealing with engineering drawings. Traditionally, the review of customer drawings needs to be executed by experienced experts before manufacture. The identification and labelling of key features were reliant on human intervention for subsequent Design for Manufacturability (DFM) or G-code programming. However, the previous method not only consumed valuable time but also introduced the potential for human errors. In this context, we introduce a high-efficiency technology for recognizing engineering drawings, automatically labelling key features, and converting unstructured data into structured data. It is noteworthy that this technology distinguishes itself from traditional methods, such as R-CNN or similar neural network approaches and differs from pre-labeled engineering drawings reliant on experts manually inputting keywords for dimensions or layers. This work is a vital step towards the realization of intelligent manufacturing. For instance, our customers can now review engineering drawings online and receive immediate feedback. This online interaction is facilitated by processing structured data, a direct output of this presented technology, with other specific modules. Furthermore, the structured data seamlessly integrates into subsequent manufacturing procedures, including notifying the supply chain, generating 3D drawings, and CNC programming. In conclusion, this technology showcases its significance in advancing our vision of intelligent manufacturing at ZY Corp.

Environmental behaviour of synthetic and natural fibre reinforced composites: A review

There has been an increasing interest in natural fibre-reinforced composites as viable alternatives to typical synthetic fibre composites as a result of increased environmental consciousness, which has led to the quest for materials that are more sustainable. This review paper aims to provide a comprehensive evaluation of the environmental performance of both natural and synthetic fibre-reinforced composites by summarizing relevant information. The article begins by discussing the advantages of natural fibres. These advantages include the fact that natural fibres are eco-friendly, Natural fibre composites demonstrate a significantly reduced carbon footprint and energy usage over their entire life cycle when compared to their glass fibre-reinforced counterparts. Furthermore, the biodegradability of natural fibres provides the opportunity for end-of-life recycling or disposal options that are more ecologically benign than those for synthetic fibre composites. This is because natural fibres are biodegradable and the research acknowledges that various factors, such as the specific fibre and matrix used, and the manufacturing procedures employed, can influence the environmental performance of natural fibre composites. Additionally, further research and development to optimize their performance and ensure their widespread adoption as sustainable alternatives to traditional composite materials. Natural fibre-reinforced composites are more environmentally friendly than traditional composite materials.

3D Printing as a Strategy to Scale-Up Biohybrid Hydrogels for T Cell Manufacture.

The emergence of cellular immunotherapy treatments is introducing more efficient strategies to combat cancer as well as autoimmune and infectious diseases. However, the cellular manufacturing procedures associated with these therapies remain costly and time-consuming, thus limiting their applicability. Recently, lymph-node-inspired PEG-heparin hydrogels have been demonstrated to improve primary human T cell culture at the laboratory scale. To go one step further in their clinical applicability, we assessed their scalability, which was successfully achieved by 3D printing. Thus, we were able to improve primary human T cell infiltration in the biohybrid PEG-heparin hydrogels, as well as increase nutrient, waste, and gas transport, resulting in higher primary human T cell proliferation rates while maintaining the phenotype. Thus, we moved one step further toward meeting the requirements needed to improve the manufacture of the cellular products used in cellular immunotherapies.

Performance Characterization of the Field Aged Asphalt Pavement Materials at Mortar Scale: Testing Method Optimization and Rheology Analysis

Performance evaluation at the asphalt mortar scale offers increased sensitivity to aging and is less affected by extraction processes comparated to asphalt mixture. Despite these benefits, there is currently a lack of standardized methods for directly processing mortar samples obtained from field mixtures. This study aims to improve and validate a manufacturing procedure for aged mortar specimens derived from field aging cores, and to evaluate the field damage level of asphalt paving materials at the mortar scale. A novel approach was developed that incorporates warm sieving, compaction, coring, and cutting to manufacture mortar specimens suitable for Dynamic Shear Rheometer (DSR) tests. This study selected mortar specimens with different service ages and conducted rheological tests, including frequency sweep tests and modified Multiple Stress Creep Recovery (MSCR) tests, to assess their rheological performance. And the significance test of all the indcies were conducted to select suitable indcies.The results show the proposed aged mortar manufacture approach can prepare eligible mortar specimens for rheology tests. The rheology test results show that several indices can distinguish different mortar types and service ages, and the indices of surface layer mortar follow a linear relationship with service age. The linear viscoelastic zone (LVE), representative shear modulus (G0), and unrecovered creep compliance at 1.6kPa (Jnr1.6) and 3.2kPa (Jnr3.2) are identified as effective indices for evaluating the behavior of field aged mortar because of their effectiveness, lower variability, and better distinction.

The Spread of Mycobacterium chimaera from Heater-Cooler Units and Infection Risk in Heart Surgery: Lessons from the Global Outbreak?

Mycobacterium chimaera (MC), a member of the Mycobacterium avium complex, can cause infections in patients after open-heart surgery due to contaminated heater-cooler units (HCUs). The transmission route of HCU-related MC infection is non-inhalational, and infection can occur in patients without previously known immune deficiency. Patients may develop endocarditis of the prosthetic valve, infection of the vascular graft, and/or manifestations of disseminated mycobacterial infection (splenomegaly, arthritis, hepatitis, nephritis, myocarditis, etc.). MC infections have serious outcomes (30-50% recurrence rate, 20-67% mortality rate). In 2015, an international outbreak of M. chimaera infections among patients undergoing cardiothoracic surgeries was associated with exposure to contaminated LivaNova 3T HCUs (formerly Stöckert 3T heater-cooler system, London, United Kingdom). In response to the global outbreak, many international agencies have issued directives and recommendations in order to reduce the risk of MC infection in cardiac surgery. Whole-genome sequencing (WGS) technology can be used to describe the global spread and dynamics of MC infections, to characterize local outbreaks, and also to identify sources of infection in hospital settings. In order to minimize the risk of contamination of HCUs and reduce the risk of patient infection, it is imperative that healthcare facilities establish a program of regular cleaning and disinfection maintenance procedures as well as monitoring of the water used and the air in the operating room, in accordance with the manufacturer's procedure.

Human neural stem cell-derived artificial organelles to improve oxidative phosphorylation

Oxidative phosphorylation (OXPHOS) in the mitochondrial inner membrane is a therapeutic target in many diseases. Neural stem cells (NSCs) show progress in improving mitochondrial dysfunction in the central nervous system (CNS). However, translating neural stem cell-based therapies to the clinic is challenged by uncontrollable biological variability or heterogeneity, hindering uniform clinical safety and efficacy evaluations. We propose a systematic top-down design based on membrane self-assembly to develop neural stem cell-derived oxidative phosphorylating artificial organelles (SAOs) for targeting the central nervous system as an alternative to NSCs. We construct human conditionally immortal clone neural stem cells (iNSCs) as parent cells and use a streamlined closed operation system to prepare neural stem cell-derived highly homogenous oxidative phosphorylating artificial organelles. These artificial organelles act as biomimetic organelles to mimic respiration chain function and perform oxidative phosphorylation, thus improving ATP synthesis deficiency and rectifying excessive mitochondrial reactive oxygen species production. Conclusively, we provide a framework for a generalizable manufacturing procedure that opens promising prospects for disease treatment.

AI-Powered Innovations in Contemporary Manufacturing Procedures: An Extensive Analysis

The industrial sector is undergoing a transformation thanks to artificial intelligence (AI), which is bringing revolutionary changes to a number of areas like robots and automation, supply chain efficiency, predictive maintenance, and quality control and assurance. This thorough analysis investigates AI's significant influence on contemporary manufacturing procedures. Artificial Intelligence (AI) improves machine capabilities in robotics and automation, creating more intelligent and flexible systems. Robots can now complete complicated tasks with more flexibility and precision thanks to AI-driven developments, which boosts manufacturing efficiency and human-robot cooperation. Another crucial area where AI has a big impact is predictive maintenance. With the use of machine learning algorithms and real-time data analysis, artificial intelligence (AI) helps manufacturers anticipate equipment faults before they happen. By taking a proactive stance, unplanned downtime is decreased, resource usage is optimized, and machinery longevity is increased. AI has a significant positive impact on quality assurance and control because to cutting-edge technologies like data analytics and computer vision. Artificial intelligence (AI) solutions facilitate predictive quality management, improve fault identification, and offer real-time monitoring. Higher quality standards, less waste, and more customer happiness are the outcomes of this. Artificial Intelligence (AI) tackles issues related to supplier performance, accurate forecasting, and inventory management in supply chain optimization. Automation and analytics powered by AI simplify supply chain processes, increase transparency, and facilitate improved decision-making, which lowers costs and increases flexibility. All things considered, integrating AI into manufacturing processes offers a strategic advantage by promoting increased accuracy, flexibility, and efficiency. The continued developments in AI technology have the potential to significantly influence how manufacturing develops in the future by creating new avenues for creativity and excellence in the sector.

Integrating Ayurvedic philosophy with modern technologies for drug research and development: A critical need of mechanistic insights for wider acceptability

Ayurveda is a holistic science emphasizing healing and maintaining harmony and balance in the body. Medicines from natural resources and in pre-defined dosage forms are integral parts of successful Ayurvedic treatment in various diseases including complex ailments, such as cancer. Ayurvedic medicines are cocktails of several active phyto-compounds and/or natural resources and no isolated/purified molecules are used in the treatment. However, various unique methods employed using natural media, such as water, lipids, buttermilk, and lemon juice, just to name a few, lead to the elimination of unwanted constituents/impurities and enhance the bioavailability and efficacy of the drug. Such plausible alterations, selection, and/or retention of signature phytocompounds in the raw materials, during the process, and in the final drug need to be studied for precise product identification and analysis. Critical standardization of the manufacturing procedures is, therefore, mandatory for quality fidelity, assurance, and optimum efficacy. Moreover, the simultaneous multi-level and/or multi-targeted actions of Ayurvedic medicines against various dysfunctions due to their complex nature makes it extremely challenging to understand the mechanistic aspects during pre-clinical and clinical studies.The present article focuses on probable challenges and ideal roadmaps for standardization and characterization of such herbal as well as metallic-mineral Ayurvedic medicines being used for various simple and complex diseases like cancer and their treatments. It is emphasized that Ayurvedic manufacturing procedures should be followed meticulously and the finished product be characterized thoroughly using advanced pharmaceutical and analytical techniques. It is also accentuated that detailed monographs or dossiers including shelf-life studies need to be officially published for knowledge dissemination and worldwide acceptance. Finally, safety and efficacy studies as per modern pharmacology ought to be conducted in suitable animal models for the judicious use of these medicines. Mainstream or adjuvant treatment of dreadful diseases such as cancer with Ayurvedic medicines will only be fruitful through rational experimentation and ethical reporting.

Revolutionizing cancer treatment: The role of radiopharmaceuticals in modern cancer therapy

AbstractRadiopharmaceutical therapy (RPT) is a precision medicine approach that involves the targeted delivery of radioactive atoms to tumor cells, representing a breakthrough strategy for cancer treatment. Radiopharmaceuticals typically consist of a small amount of radioactive material, a radionuclide, paired with a chemical that specifically targets the cell. Some radionuclides naturally target specific cells or biological processes without the need for modification. RPT is a novel cancer treatment method that offers various advantages over current traditional treatment approaches. One of the primary advantages of RPT is its ability to target cancer cells, including those in metastatic areas. Another key advantage of RPT is that radiation can be delivered systemically, locally, or physiologically to specific cells internally rather than being applied externally. Moreover, radiotracer imaging can be utilized to determine radiopharmaceutical absorption in target tissues before providing a therapeutic dose. Compared to all other cancer treatment approaches, RPT has demonstrated high efficacy with minimal toxicity. The recent approval of multiple RPT medicines by the US Food and Drug Administration highlights the tremendous potential of this treatment. This article provides a detailed review of RPT, including insights into manufacturing procedures, safety measures, and its applications in cancer therapy.

Product development and characterization of a lipid-based Ayurvedic polyherbal formulation: Kalyanaka Ghrita

BackgroundKalyanaka Ghrita (KG) is polyherbal oleaginous medicament consisting of extracts from twenty-eight different plants, indicated for management of psychosomatic disorders like Unmada (Schizophrenia), Apasmara (Epilepsy) and numerous other ailments. ObjectiveTo develop and validate standard manufacturing procedure of KG by following Ayurvedic principles in three batches to ensure process uniformity and standards. Materials and methodsThree batches of KG were prepared by adopting principles of Ashtanga Hrudya and Ayurvedic Formulary of India to ensure consistency in manufacturing process. Observations during process such as temperature, duration were recorded. KG was subjected to chief desired characteristics, organoleptic (color, odour, taste, texture, touch), physicochemical (acid value, peroxide value, iodine value, saponification value, loss on drying, refractive index, specific gravity, mineral oil, rancidity test, viscosity) as per pharmacopeial standard. Chromatographic screening and fingerprinting of KG were conducted through GCMS whereas quantification of curcumin and chebulagic acid biomarkers were assessed through HPLC. ResultsAverage yield of KG was 83.41%, with average intermittent heating duration of 20.35 h subsequently divided into three days. Temperature throughout preparation ranged from 66 °C to 101 °C. KG was pale olive in colour, exhibiting pleasant taste, characteristic smell, and soft texture. Organoleptic and physicochemical characters were comparable for three batches of KG while safety parameters were found within permissible limits. ConclusionPharmaceutical standardization of Kalyanaka Ghrita is necessary for establishing biological and chemical profile of formulations. Present study recommends use of coarse powdered ingredients for optimal yield during pharmaceutical process, and heating up to Madhyama Paka stage calibrated over three days with average temperature of 85 °C. The data obtained from this study may contribute to future research and development activities, serving as a basis for manufacturing standards of KG.

Continuous fabrication of triboelectric/piezoelectric hybrid yarns with high output for self-powered wearable sensors

Yarn-based nanogenerators exhibit potential for use in self-powered wearable sensors. However, their current limitations include intricate manufacturing procedures, low electrical output performance, and a restricted level of reliability. Here, we present a continuous fabrication approach for fabricating triboelectric/piezoelectric hybrid nanogenerators utilizing yarns with integrated exceptional performance. The continuous production process exhibits the attributes of one-step forming, wherein piezoelectric nanofibers and triboelectric silicone rubber covering are simultaneously and effectively attached to a single yarn to create yarn-based hybrid nanogenerators. The hybrid yarn demonstrates exceptional electrical output performance by harnessing the advantages of both piezoelectric and triboelectric effects, resulting in a power density of 26.72 μW/m2 at 17 MΩ. Demonstrating high sensitivity, stability, and mechanical resilience, yarn-based hybrid nanogenerators are suitable for self-powered wearable sensors, enabling applications in Morse code recognition and gait detection. This innovation in yarn-based nanogenerators broadens their scope, heralding new possibilities in the energy-harvesting device and wearable technology.

Impact of AI on Manufacturing and Quality Assurance in Medical Device and Pharmaceuticals Industry

Global health and well-being largely depend on the pharmaceutical and medical device industries. Manufacturing and quality assurance (QA) processes are crucial to maintaining product efficacy, safety, and regulatory compliance in these sectors. Artificial intelligence (AI) integration presents ground-breaking opportunities to enhance these processes. This study aims to systematically assess the impact of AI on manufacturing and QA in these pharmaceutical and medical device industries. It examines the benefits, challenges, and ethical and legal implications of integrating AI. It offers a thorough understanding of how AI technology can and has been successfully integrated to enhance business operations. An extensive literature analysis was carried out to investigate AI's application, role, benefits, and challenges in manufacturing and quality assurance processes in both industries. Research was also conducted on emerging trends, future developments, and regulatory issues. Increased productivity, early detection of defects, safer and higher-quality goods, improved regulatory compliance, reduced costs, and more flexibility and scalability are some advantages of AI technologies. However, significant obstacles are also to overcome, such as high capital costs, data quality and availability issues, legacy system integration, ethical concerns about bias and data privacy, difficulties with regulatory compliance, and a lack of AI-skilled workers. Case studies show how AI has been utilized to guarantee regulatory compliance and optimize processes. AI integration has much to offer the pharmaceutical and medical device industries in terms of improved manufacturing and quality assurance procedures. By addressing restrictions and seizing novel opportunities, these industries can use AI's transformative potential to support innovation, enhance product quality and safety, ensure regulatory compliance, and improve global health outcomes.

MXene Based Flame Retardant and Electrically Conductive Polymer Coatings.

Modern polymer coatings possess tremendous multifunctionalities and have attracted immense research interest in recent decades. However, with the expeditious development of technologies and industries, there is a vast demand for the flame retardancy and electrical conductivity of engineered polymer coatings. Traditional functional materials that render the polymer coatings with these properties require a sophisticated fabrication process, and their high mass gains can be a critical issue for weight-sensitive applications. In recent years, massive research has been conducted on a newly emerged two-dimensional (2D) nanosize material family, MXene. Due to the excellent electrical conductivity, flame retardancy, and lightweightness, investigations have been launched to synthesise MXene-based polymer coatings. Consequently, we performed a step-by-step review of MXene-involved polymer coatings, from solely attaching MXene to the substrate surface to the multilayered coating of modified MXene with other components. This review examines the performances of the fire safety enhancement and electrical conductivity as well as the feasibility of the manufacturing procedures of the as-prepared polymer composites. Additionally, the fabricated polymer coatings' dual property mechanisms are well-demonstrated. Finally, the prospect of MXene participating in polymer coatings to render flame retardancy and electrical conductivity is forecasted.

Next-generation BCMA-targeted chimeric antigen receptor CARTemis-1: the impact of manufacturing procedure on CAR T-cell features.

CAR therapy targeting BCMA is under investigation as treatment for multiple myeloma. However, given the lack of plateau in most studies, pursuing more effective alternatives is imperative. We present the preclinical and clinical validation of a new optimized anti-BCMA CAR (CARTemis-1). In addition, we explored how the manufacturing process could impact CAR-T cell product quality and fitness. CARTemis-1 optimizations were evaluated at the preclinical level both, in vitro and in vivo. CARTemis-1 generation was validated under GMP conditions, studying the dynamics of the immunophenotype from leukapheresis to final product. Here, we studied the impact of the manufacturing process on CAR-T cells to define optimal cell culture protocol and expansion time to increase product fitness. Two different versions of CARTemis-1 with different spacers were compared. The longer version showed increased cytotoxicity. The incorporation of the safety-gene EGFRt into the CARTemis-1 structure can be used as a monitoring marker. CARTemis-1 showed no inhibition by soluble BCMA and presents potent antitumor effects both in vitro and in vivo. Expansion with IL-2 or IL-7/IL-15 was compared, revealing greater proliferation, less differentiation, and less exhaustion with IL-7/IL-15. Three consecutive batches of CARTemis-1 were produced under GMP guidelines meeting all the required specifications. CARTemis-1 cells manufactured under GMP conditions showed increased memory subpopulations, reduced exhaustion markers and selective antitumor efficacy against MM cell lines and primary myeloma cells. The optimal release time points for obtaining the best fit product were > 6 and < 10 days (days 8-10). CARTemis-1 has been rationally designed to increase antitumor efficacy, overcome sBCMA inhibition, and incorporate the expression of a safety-gene. The generation of CARTemis-1 was successfully validated under GMP standards. A phase I/II clinical trial for patients with multiple myeloma will be conducted (EuCT number 2022-503063-15-00).

Evaluation of Basal Plane Dislocation Behavior near Epilayer and Substrate Interface

An essential silicon carbide (SiC) manufacturing procedure for eliminating bipolar degradation in a SiC device is the detection of the basal plane dislocation (BPD) causing the phenomenon. In this work, we employed the mirror electron microscope (MEM) technique, which has higher resolution than photoluminescence. The MEM provided results for the detection of short BPDs without conversion to threading edge dislocation at the epi/sub interface. In addition, a considerable number of short BPDs were observed in the epilayer grown with the improved method, and the conversion ratio around the buffer layer could be derived.

Low cross-talk optical addressing of trapped-ion qubits using a novel integrated photonic chip

Individual optical addressing in chains of trapped atomic ions requires the generation of many small, closely spaced beams with low cross-talk. Furthermore, implementing parallel operations necessitates phase, frequency, and amplitude control of each individual beam. Here, we present a scalable method for achieving all of these capabilities using a high-performance integrated photonic chip coupled to a network of optical fibre components. The chip design results in very low cross-talk between neighbouring channels even at the micrometre-scale spacing by implementing a very high refractive index contrast between the channel core and cladding. Furthermore, the photonic chip manufacturing procedure is highly flexible, allowing for the creation of devices with an arbitrary number of channels as well as non-uniform channel spacing at the chip output. We present the system used to integrate the chip within our ion trap apparatus and characterise the performance of the full individual addressing setup using a single trapped ion as a light-field sensor. Our measurements showed intensity cross-talk below ~10–3 across the chip, with minimum observed cross-talk as low as ~10–5.

Glycopolymeric Micellar Nanoparticles for Platelet-Mediated Tumor-Targeted Delivery of Docetaxel for Cancer Therapy.

The high level of accumulation of therapeutic agents in tumors is crucial for cancer treatment. Compared to the passive tumor-targeting effect, active tumor-targeting delivery systems, primarily mediated by peptides with high production costs and reduced circulation time, are highly desired. Platelet-driven technologies have opened new avenues for targeted drug delivery prevalently through a membrane coating strategy that involves intricate manufacturing procedures or the fucoidan-mediated hitchhiking method with limited platelet affinity. Here, a novel type of amphiphilic glycopolymer self-assembled micellar nanoparticle has been developed to adhere to naturally activated platelets in the blood. The simultaneous integration of fucose and sialic acid segments into glycopolymers enables closer mimicry of the structure of P-selectin glycoprotein ligand-1 (PSGL-1), thereby increasing the affinity for activated platelets. It results in the formation of glycopolymeric micelle-platelet hybrids, facilitating targeted drug delivery to tumors. The selective platelet-assisted cellular uptake of docetaxel (DTX)-loaded glycopolymeric micelles leads to lower IC50 values against 4T1 cells than that of free DTX. The directed tumor-targeting effect of activated platelets has significantly improved the tumor accumulation capacity of the glycopolymeric nanoparticles, with up to 21.0% found in tumors within the initial 0.2 h. Additionally, with acid-responsive drug release and inherent antimetastasis properties, the glycopolymeric nanoparticles ensured potent therapeutic efficacy, prolonged survival time, and reduced cardiotoxicity, presenting a new and unexplored strategy for platelet-directed drug delivery to tumors, showing promising prospects in treating localized tumors and preventing tumor metastasis.

Does outsourcing enhance consumer services and profitability of a dual-channel retailing?

In the era of digital commerce, the concept of dual-channel retailing has attracted increased attention. Dual-channel retailing increases the importance of outsourcing for an imperfect production process to enhance customer satisfaction. This study explores a sustainable dual-channel retailing strategies for an imperfect production process under a flexible production system. The manufacturer runs a production process prone to defects utilizes both offline and online channels for product sales. The manufacturer contemplates green investments to enhance the production efficiency and reduce waste and carbon emissions, alongside the possibility of outsourcing a portion of production to a partner. A mathematical model is developed to accounts for these factors and analyzes the optimal allocation of products between channels, pricing strategies, production rates, and investments amount to reduce carbon emissions. The model incorporates demand sensitiveness to green practices and channel's selling price. Results of this research are directed towards offering significant perspectives for organizations that aspire to attain a harmonious equilibrium among financial profitability, ecological sustainability, and addressing deficiencies in their manufacturing procedures in a dual-channel retail setting through subcontracting. Numerical illustrations exhibit that partial outsourcing enhances system's profit by 2.03%, whereas investments to reduce carbon emissions enhance the profit by 4.95%. Flexibility in the production process helps to increase the profit by 13.50%, and channel coordination helps to enhance the profit by 38.54%.