Search Results (4,166)

Recent progress in tumor immunotherapy highlights the important role of the immune system in combating various cancers. Traditionally designed to protect against infectious diseases, vaccines are now being adapted to stimulate immune responses against tumor-specific neoantigens. Both preclinical studies and clinical trials have explored innovative approaches for identifying neoantigens and optimizing vaccine design, advancing the field of personalized oncology. Among these, DNA-based vaccines have become a particularly attractive approach for cancer immunotherapy. This evolution has been driven by improvements in molecular biology techniques, including more precise methods for detecting tumor-specific mutations, computational tools for predicting immunogenic antigens, and novel platforms for delivering nucleic acid vaccines. Personalized DNA vaccines are typically developed through a complex, multi-step process that involves sequencing a patient’s tumor, computational analysis to identify potential targets, and custom vaccine production. In this review, we examine the use of both shared tumor antigens and individualized neoantigens in cancer vaccine development. We outline strategies for neoantigen identification that provide insights into tumor-specific alterations. Furthermore, we highlight recent advances in DNA vaccine technologies, address the current limitations facing cancer vaccines, propose strategies to overcome these challenges, and consider key clinical and technical factors for successful implementation. Full article

Omni-channel retailers arise to address the deficiencies in consumers’ online shopping experiences; the resulting competition between such retailers and traditional online platforms presents substantial challenges for green product manufacturers. A three-level game model is established to examine a manufacturer’s green contract design (product pricing and greenness determination) and mode selection under the competition between an online platform and a new retailer providing omni-channel services to end customers. The manufacturer can select between two modes: supplying a green product to the online platform and new retailer (mode RR) or selling it directly through the online platform and reselling it to the new retailer (mode PR). Our findings indicate that, first, even if the relationship between the manufacturer and new retailer has changed from cooperation under mode RR to competition and cooperation under mode PR, the manufacturer still favors two-channel sales over single-channel sales and affects consumer channel choices to adjust market shares through mode selection. Second, regarding the impacts of the key parameters on the manufacturer, downstream e-commerce platform retailers and environment are intricate and nuanced. While raising the omni-channel service level enhances profitability in the new retailer across both modes, its environmental impacts differ significantly between them. Additionally, it can harm the online platform in some cases. Nevertheless, when the parameters fall within suitable ranges, the manufacturer and both downstream retailers have a consistent preference for improved omni-channel services under both modes. Finally, there is a significant divergence in mode preferences among the manufacturer and both downstream platform retailers. Due to the first-mover advantage, the manufacturer opts for mode RR over mode PR in most cases. Notably, within a specific range of parameters, they consistently prefer mode RR, which also proves beneficial for the environment, resulting in a Pareto optimal outcome. This proposes a concrete cooperation mechanism among the manufacturer, retailers, and consumers from quantitative insights, which can promote green products to achieve the objective of low-carbon environmental protection. Full article

Polyhydroxyalkanoate (PHA) bioplastics are produced from wastewater as a carbon recovery strategy. However, the tuneable characteristics of PHAs and wastewater biorefinery potential have not been comprehensively reviewed. The aim of this study is to review the main challenges and strategies for carbon recovery from wastewater feedstocks via PHA production, assessing potential target biopolymer applications. Diverse PHA-accumulating prokaryotes metabolize organic pollutants present in wastewater through different metabolic pathways, determining the biopolymer characteristics. The synthesis of PHAs using mixed microbial cultures with wastewater feedstocks derived from municipal, agro-industrial, food processing, lignocellulosic biomass processing and biofuel production activities are described. Acidogenic fermentation of wastewater feedstocks and mixed microbial culture enrichment are key steps in order to enhance PHA productivity and determine biopolymer properties towards customized bioplastics for specific applications. Biorefinery of PHA copolymers and extracellular polysaccharides (EPSs), including alginate-like polysaccharides, are alternatives to enhance the value-chain of carbon recovery from wastewater. PHAs and EPSs exhibit a wide repertoire of applications with distinct safety control requirements; hence, coupling biopolymer production demonstrations with target applications is crucial to move towards full-scale applications. This study discusses the relationship between the metabolic basis of PHA synthesis and composition, wastewater type, and target applications, describing the potential to maximize carbon resource valorisation. Full article

The sexual generation of Schlechtendalia chinensis (Bell) is pivotal for gallnut yield yet cannot feed due to mouthpart degeneration. Could respiratory metabolic rate (RMR) modulation compensate for nutritional deficits? We quantified the RMR across key developmental stages of sexual morphs (including parental sexuparae and progeny fundatrices) using an LI-6400XT portable photosynthesis system equipped with a customized insect respiration chamber (6400-89). All morphotypes exhibited significantly lower nocturnal RMRs compared to their diurnal rates (p < 0.05), while RMRs did not differ significantly between morning (9:00–12:00) and afternoon (14:00–17:00) (p > 0.05). Significant RMR variation occurred among morphotypes: females and sexuparae displayed the lowest rates, fundatrices were intermediate, and males exhibited remarkably elevated rates (2–3 times higher than those of females or sexuparae). Both sexes showed a characteristic RMR trajectory: elevated at birth and declining during early postnatal development, followed by a gradual resurgence that culminated in peak values on postnatal day 8, coinciding with mating. This physiological zenith was immediately succeeded by marked respiratory metabolic downregulation following copulation, with RMRs decreasing substantially during the post-copulatory phase. Our findings demonstrate significant intergenerational and intersexual RMR differentiation. This research addresses critical knowledge gaps in the respiratory metabolism of S. chinensis, is the first to elucidate a nutrient adaptation strategy through respiratory metabolic regulation under non-trophic conditions, and provides actionable insights for optimizing gallnut production in controlled cultivation systems. Full article

Modern custom machine construction and automation projects face pressure to shorten innovation cycles, reduce durations, and manage growing system complexity. Traditional methods like Waterfall and V-Model have limits where end-to-end data traceability is vital throughout the product life cycle. This study introduces the implementation of a web application that incorporates a model-based design approach to assess its applicability and effectiveness in conceptual design scenarios. At the heart of this approach is the Case-Based Axiomatic Design Assistant (CADA), which utilizes Axiomatic Design principles to break down complex tasks into structured, analyzable sub-concepts. It also incorporates Case-Based Reasoning (CBR) to systematically store and reuse design knowledge. The effectiveness of the visual assistant was evaluated through expert-led assessments across different fields. The results revealed a significant reduction in design effort when utilising prior knowledge, thus validating both the efficiency of CADA as a model and the effectiveness of its implementation within a user-centric application, highlighting its collaborative features. The findings support this approach as a scalable solution for enhancing conceptual design quality, facilitating knowledge reuse, and promoting agile development. Full article

This study examines how the initiation of monetary compensation and the sincerity of apologies influence customers’ repurchase intentions after receiving products with minor defects, and how these effects are moderated by consumer pickiness and the e-store’s reputation. Two scenario-based, between-subjects online experiments were conducted in China via the Wenjuanxing online survey platform, with participants voluntarily taking part in exchange for monetary compensation. We propose that consumers have a higher repurchase intention when online customer service initiatively offers monetary compensation (vs. passive vs. no compensation) and that the effect of monetary compensation modes can be enhanced by a serious apology from customer service. Building on these findings, Study 1 (n = 330) reveals that picky consumers are more sensitive to the enhanced effect of initiative monetary compensation on repurchase intentions under serious apologies. Moreover, Study 2 (n = 537) confirms that consumers are more stringent in their expectations of high-reputation stores, whereas low-reputation stores can achieve similar positive effects with casual apologies that high-reputation stores only obtain through serious apologies. This study provides theoretical support for the importance of the initiation of actions and sincerity in service recovery and offers guidance for businesses dealing with picky consumers. Full article

Financial institutions, researchers, and policymakers are taking steps to promote financial inclusion, a crucial aspect for social and economic development. This study explores the extent of financial inclusion (FI) in Zimbabwe’s commercial banks. This study employed a mixed-methods approach. A relationship mapping was conducted on the bank customers’ survey, and a thematic analysis was performed on bank executives to evaluate bank challenges and strategies. The findings confirmed positive strides towards achieving financial inclusion. Gaps in financial inclusion were identified in the high rate of people using informal channels and the limited policies in creating a conducive environment for financial inclusion. The study contributes to the ongoing debate by the World Bank in support of financial inclusion as an effective solution for countries like Zimbabwe, which is experiencing a severe macro crisis. The study adds to the emerging financial inclusion literature, proposing solutions to reduce financial exclusion in developing economies. Based on the study findings, policymakers should create a conducive environment for commercial banks and consumers of financial products and services in Zimbabwe. Full article

Ensuring optimal adhesive curing during plywood and LVL (Layered Veneer Lumber) hot pressing requires accurate knowledge of internal temperature distribution, which is often difficult to assess using conventional surface-based measurements. This study introduces a custom-developed multi-layer smart sensor network capable of in situ, real-time temperature profiling across LVL layers during industrial hot pressing. The system integrates miniature embedded sensors and proprietary data acquisition software, enabling the simultaneous multi-point monitoring of thermal dynamics with a high temporal resolution. Experiments were performed on LVL panels of varying thicknesses, applying industry-standard pressing schedules derived from conventional calculation rules. Despite adherence to prescribed pressing times, results reveal significant core temperature deficits in thicker panels, potentially compromising adhesive gelation and overall bonding quality. These findings underline the need to revisit the pressing time determination for thicker products and demonstrate the potential of advanced sensing technologies to support adaptive process control. The proposed approach contributes to smart manufacturing and the remote-like monitoring of internal thermal states, providing valuable insights for enhancing product performance and industrial process efficiency. Full article

Lignocellulosic agro-forestry residues (LARs), such as rice straw, sugarcane bagasse, and wood wastes, are abundant and low-cost feedstocks for polyhydroxyalkanoate (PHA) bioplastics. However, their complex cellulose–hemicellulose–lignin matrix requires integrated valorization strategies. This review presents a dual-framework approach: “pretreatment–co-substrate compatibility” and “pretreatment–microbial platform matching”, to align advanced pretreatment methods (including deacetylation–microwave integration, deep eutectic solvents, and non-sterilized lignin recovery) with engineered or extremophilic microbial hosts. A “metabolic interaction” perspective on co-substrate fermentation, encompassing dynamic carbon flux allocation, synthetic consortia cooperation, and one-pot process coupling, is used to elevate PHA titers and tailor copolymer composition. In addition, we synthesize comprehensive kinetic analyses from the literature that elucidate microbial growth, substrate consumption, and dynamic carbon flux allocation under feast–famine conditions, thereby informing process optimization and scalability. Microbial platforms are reclassified as broad-substrate, process-compatible, or product-customized categories to emphasize adaptive evolution, CRISPR-guided precision design, and consortia engineering. Finally, next-generation techno-economic analyses, embracing multi-product integration, regional adaptation, and carbon-efficiency metrics, are surveyed to chart viable paths for scaling LAR-to-PHA into circular bioeconomy manufacturing. Full article

Egg weight monitoring provides critical data for calculating the feed-to-egg ratio, and improving poultry farming efficiency. Installing a computer vision monitoring system in egg collection systems enables efficient and low-cost automated egg weight measurement. However, its accuracy is compromised by egg clustering during transportation and low-contrast edges, which limits the widespread adoption of such methods. To address this, we propose an egg measurement method based on a computer vision and multi-feature extraction and regression approach. The proposed pipeline integrates two artificial neural networks: Central differential-EfficientViT YOLO (CEV-YOLO) and Egg Weight Measurement Network (EWM-Net). CEV-YOLO is an enhanced version of YOLOv11, incorporating central differential convolution (CDC) and efficient Vision Transformer (EfficientViT), enabling accurate pixel-level egg segmentation in the presence of occlusions and low-contrast edges. EWM-Net is a custom-designed neural network that utilizes the segmented egg masks to perform advanced feature extraction and precise weight estimation. Experimental results show that CEV-YOLO outperforms other YOLO-based models in egg segmentation, with a precision of 98.9%, a recall of 97.5%, and an Average Precision (AP) at an Intersection over Union (IoU) threshold of 0.9 (AP90) of 89.8%. EWM-Net achieves a mean absolute error (MAE) of 0.88 g and an R² of 0.926 in egg weight measurement, outperforming six mainstream regression models. This study provides a practical and automated solution for precise egg weight measurement in practical production scenarios, which is expected to improve the accuracy and efficiency of feed-to-egg ratio measurement in laying hen farms. Full article

The cultural landscape of Gubeikou, with distinct historical stratification and event-relatedness, bears unique value. Against the backdrop of increasingly prominent themes of cultural heritage development and transformation, research on Gubeikou’s cultural landscapes remains fragmented and lacking in depth. This research explores its evolution mechanism via historical events to fill gaps. This study takes Gubeikou Town as the research object, applies the text analysis method to sort and categorize 302 historical events, summarizes 12 event types, identifies 19 landscape elements, and constructs a data matrix based on co-occurrence frequencies. It performs clustering analysis on these using Principal Component Analysis (PCA) and Agglomerative Hierarchical Clustering (AHC), while integrating historical and geographical data. Findings: (1) The landscape evolution of Gubeikou can be divided into four main stages: the military embryonic period, the functional expansion period, the system maturity period, and the multi-element integration period. (2) The dynamic evolutionary trajectory of the correlation between its landscapes and events shows that the core factors affecting the evolution of cultural landscapes in each period not only maintain the dominance of military elements throughout the evolutionary process but also integrate diverse elements like economy, culture, and folk customs with social development, presenting the characteristics of composite evolution. (3) The landscape evolution is driven by the “primary–secondary synergy” dynamic structure composed of four types of activities: military–political, transportation, production–trade, and construction. It is the product of the coupling effect of political goals, social operation, and geographical conditions. This study provides a basis for the sustainable protection and utilization of Gubeikou, and also offers a reference for other regions. Full article

Antimicrobial resistance (AMR) is a critical global health challenge that affects both human and animal populations. In accordance with the One Health paradigm, AMR has been monitored in Italy since 2014 in major zoonotic pathogens and opportunistic commensal bacteria from animal productions, in the frame of the EU Harmonized Monitoring Program for AMR (according to EU Decision 2013/652, repealed by EU Decision 2020/1729), conducted by the Italian National Reference Center (CRN-AR) and National Reference Laboratory (NRL-AR) for antimicrobial resistance at the “Istituto Zooprofilattico Sperimentale del Lazio e della Toscana (IZSLT)” (on behalf of the Italian Ministry of Health). Among all monitored bacterial species, the commensal Enterococcus (E.) faecium and E. faecalis have emerged as opportunistic human pathogens with increasing AMR profiles. To address this challenge, the CRN-AR and NRL-AR have developed a custom bioinformatic pipeline, named Enteroflow, which enables the efficient analysis of high-throughput sequencing (HTS) data for the genomic characterization of E. faecium/faecalis isolates. A pivotal feature in this tool is the integration of Nextflow’s workflow manager and Domain Specific Language (DSL), ensuring the reproducibility and scalability of genomic analyses while allowing the monitoring of processes and computational performances. The list of tools included in the workflow spans from short read assemblers to genomic characterization tools for AMR and virulence gene detection and plasmid replicon typing, with results also being combined in structured and usable reports. These developments represent a major step forward in supporting the surveillance efforts and mitigation strategies for AMR in zoonotic and commensal bacteria. Full article

In retail enterprises, employee well-being is recognized as a key factor influencing service quality and operational sustainability. While prior research has extensively investigated enterprise-centric approaches to improving employee well-being, little scholarly attention has been devoted to understanding the effects of customer participation and service scene innovation on employee well-being. Employing a case study methodology, this research investigates a Chinese exemplary retail enterprise “Pang Donglai”, exploring how retail enterprises can leverage service scene innovation to improve employee well-being from the perspective of scene innovation. The findings reveal that service scene innovation in retail enterprises can be categorized into three types: empowerment-oriented scene innovation, autonomy-oriented shopping scene innovation, and thematic display scene innovation. These innovations facilitate empathetic interactions between employees and customers, effectively enhancing employee well-being and creating a virtuous cycle of value co-creation among the enterprise, employees, and customers. Therefore, retail enterprises can continuously improve the working situation of employees, the display of products, and the shopping environment of customers, in order to enhance employee well-being and thus improve their voluntary behaviour and its sustainability. This study provides empirical insights into how retail enterprises can enhance employee well-being through service scene innovation, thereby contributing to the improvement of business performance. Full article

Furniture is an integral part of daily life. Its comfort and usability are key factors that define its success. In recent years, there has been increasing demand for applications that drive businesses toward Industry 4.0. These applications aim to improve productivity through greater automation in both 3D modeling and fabrication processes. This research aims to develop a Computer Aided Design (CAD) platform that automates the design and manufacturing of furniture. The platform is based on visual programming using Grasshopper 3D™ and provides a solid foundation for processing different geometric shapes. These shapes can be customized according to the user’s preferences. The platform’s innovation lies in its ability to process complex geometries with a fully automated algorithm. Once the initial parameters are set, the algorithm generates the results. The input data includes an initial geometry, which can be highly complex. Additionally, a set of construction parameters is introduced, leading to multiple alternative design solutions based on the same initial geometry. The designer and user can select their final choice, and all resulting design and manufacturing outcomes are automatically generated. These outcomes include 3D part models, 3D assembly files, Bill of Materials, G-code for CNC machining, and nesting capabilities for improved material efficiency. The platform ensures high-quality performance. The results of the study show that the platform successfully works with different geometries. Moreover, the study is significant as the Industry 4.0 transformation moves toward more automated design processes. Full article

The spatial layout of farmland involves coordinated planning across diverse functional zones. Irregular land boundaries and functional demands pose challenges to traditional CAD-based workflows and general optimization algorithms. To address these limitations, we propose an interactive farmland layout system based on the Graphic-Guided Evolutionary Layout (GGEL) algorithm. GGEL not only introduces a graph-based spatial pruning and encoding strategy to improve search efficiency, but also performs real-time spatial overlap detection based on functional region boundaries to ensure layout feasibility. Additionally, an interactive module enables real-time user customization to accommodate specific planning needs. Experimental results demonstrate that the system can efficiently generate complete multi-region layouts, significantly enhancing design productivity. A user study with 20 agricultural park experts confirms the system’s usability and effectiveness. This study highlights the potential of integrating evolutionary algorithms with topological graph representations to address the complex spatial planning requirements of digital agricultural parks. Full article