Search Results (72)

Investigating the volatiles isolated from a commercial spirulina (Arthrospira platensis) dietary supplement by gas chromatography–olfactometry (GC–O) in combination with an aroma extract dilution analysis (AEDA) resulted in 29 odor events with flavor dilution (FD) factors between 8 and 2048. Identification experiments, including various offline and online fractionation approaches, led to the structure assignment of 30 odorants, among which the most potent were sweaty 2- and 3-methylbutanoic acid (FD 2048), roasty, earthy, shrimp-like 2-ethyl-3,5-dimethylpyrazine (FD 2048), vinegar-like acetic acid (FD 1024), and floral, violet-like β-ionone (FD 1024). Static headspace dilution analysis revealed sulfuric, cabbage-like methanethiol (FD factor ≥ 32) as an additional potent odorant. In summary, 31 important spirulina odorants were identified in this study, and 14 were reported for the first time as spirulina constituents. Our data will provide a basis for future odor optimization of spirulina-based food products. Full article

This paper investigates sustainable decision systems within green E-business models by analyzing how different O2O (online-to-offline) fulfillment structures affect emission-reduction efforts and pricing strategies in a two-tier supply chain consisting of a manufacturer and a new retailer. Three practical sales formats—package self-pickup, nearby delivery, and hybrid—are modeled using Stackelberg game frameworks that incorporate key factors such as inconvenience cost, logistics cost, processing fees, and emission-reduction coefficients. Results show that the manufacturer’s emission-reduction decisions and both parties’ pricing strategies are highly sensitive to cost conditions and consumer preferences. Specifically, higher inconvenience and abatement costs consistently reduce profitability and emission efforts; the hybrid model exhibits threshold-dependent advantages over single-mode strategies in terms of carbon efficiency and economic returns; and consumer green preference and distance sensitivity jointly shape optimal channel configurations. Robustness analysis confirms the model’s stability under varying parameter conditions. These insights provide theoretical and practical guidance for firms seeking to develop adaptive, low-carbon fulfillment strategies that align with sustainability goals and market demands. Full article

This study takes the dual-channel fresh product supply chain involving the participation of third-party logistics (3PL) as the background to explore how 3PL makes choices between homogeneous and differentiated logistics service strategies and how the supply chain formulates optimal decisions under different logistics service strategies to achieve maximum benefits. This paper constructs a sequential game model of the three-tier supply chain composed of 3PL, a supplier, and a retailer; uses the consumer utility function to describe market demand; and considers different logistics service strategies adopted by 3PL. It compares and analyzes the equilibrium strategies under the traditional retail channel (O Model), the homogeneous cold-chain service dual-channel model (D1 Model), and the differentiated cold-chain service dual-channel model (D2 Model). The results show the following: (1) The D1 Model reduces the transportation cost of the supply chain through economies of scale. Under the D2 Model, the transportation and sales prices of the offline channels are higher than those of the online channels, while the online marketing effort is higher than that of the offline channels. (2) The profits generated by the dual-channel models (D1 Model and D2 Model) are both higher than those of O Model. In most cases, the D1 Model generates the highest system profit. However, in scenarios where consumers are highly sensitive to freshness and marketing efforts, the system profit of the D2 Model is higher than that of the D1 Model. (3) The supply chain has lower pricing and effort input when consumers are more sensitive to prices and higher pricing and effort input when consumers are more sensitive to freshness. These findings contribute valuable insights to the field of supply chain management, particularly in the context of fresh product supply chains involving 3PL. They underscore the importance of considering consumer behavior and logistics service strategies in optimizing supply chain performance and highlight the potential trade-offs between standardization and differentiation in logistics services. Full article

In the context of the global environment, the rapid advancement of Internet technology has facilitated a transition from traditional offline to online modes for corporate social responsibility (CSR) activities, leading to the emergence of virtual CSR co-creation initiatives. A crucial challenge for enterprises engaging in such activities lies in enhancing consumer participation and retention rates. This study constructs a mediation effect model incorporating emotional factors, interaction factors, social presence, and consumer willingness to participate, grounded in the Stimulus–Organism–Response (S-O-R) model. Based on data collected from 232 consumers in China, this study reveals that identification, enthusiasm, and satisfaction exert positive influences on consumer willingness to participate. Additionally, social presence positively affects willingness to participate and acts as a mediator between community platform interaction, offline interaction, and willingness to participate. Full article

Several strategies, including UV detection with a diode array detector (DAD), laser-induced fluorescence (LIF), derivatization reactions, the use of micelles in the separation buffer, as well as online preconcentration techniques based on pressure-assisted electrokinetic injection (PAEKI), and offline preconcentration using solid-phase extraction (SPE) columns containing quaternary amine groups with a chloride counterion, were investigated for the simultaneous separation and signal amplification of free thyroid hormones (THs) in biological samples. Moreover, a sensitive method for the quantification of THs in selected biological samples using micellar electrokinetic capillary chromatography with LIF detection (MEKC-LIF) was developed. The THs present in biological samples (L-tyrosine, T2, T3, rT3, T4, and DIT) were successfully separated in less than 10 min. The analytes were separated following a derivatization procedure with fluorescein isothiocyanate isomer I (FITC). A background electrolyte (BGE) composed of 20 mM sodium tetraborate (Na₂B₄O₇) and 20 mM sodium dodecyl sulphate (SDS) was employed. Key validation parameters such as linearity, precision, limits of detection (LOD), and limits of quantification (LOQ) were determined. The use of PAEKI for the electrophoretic determination of free THs demonstrates significant potential for monitoring these hormones in real urine samples due to its high sensitivity and efficiency. Full article

Thermal oils have been utilized as heat transfer fluids for several decades in many applications, including industrial facilities, power plants and solar receiver systems. Despite their large employment, very few data are available about oils behavior under thermal stress and related degradation processes. For these reasons, the thermal stability of a silicone-based diathermic oil, Bluesil FLD 550 HT, was investigated in the present work. A laboratory-scale set-up was assessed to perform controlled heating tests, and fresh and thermally aged oils samples were analyzed to determine changes in chemical composition and thermo-physical features. Degradation products in the gaseous and vapor phase were also detected and analyzed by online and offline measurements. The obtained results are compared with the ones present for aromatic oils, largely employed as heat transfer media. Bluesil showed a higher thermal resistance compared to aromatic materials, and, thanks to its low volatility together with a high chemical stability, it was successfully tested up to 500 °C. According to its polymeric structure, thermal degradation processes occur mainly through Si-O bond scission, leading to both the segmentation of silicone chains and the formation of cross-linked species as byproducts. Full article

Environmental protection and low-carbon life are the focus of global attention. This paper adopts Stackelberg’s game method to discuss channel selection. Two decision models are involved: (1) model P represents dual-channel structure of the manufacturer, and (2) model O represents dual-channel structure of the retailer. We examined the optimal pricing strategy, and profit distribution among stakeholders. This research showed that, compared to model O, model D always sells more products, and model D has a higher (manufacturer)/lower (retailer) profits than model O. The retailer’s offline price exhibits a linear decline. At the point of intersection (0.28, 45.5), the price in both models converge to an identical value. From an environmental perspective, model D is more environmentally friendly than model O when unit carbon price is small. Furthermore, the emission reduction rate is higher if consumers’ online preference coefficient is not high in model D. Through the lens of social welfare, the sales strategies employed in model O yield higher social welfare benefits compared to those in model D. For the entire supply chain, model O is the optimal choice if they focus on environmental performance and social welfare. The research provides application guidance for the sustainable development of enterprises. Full article

Previous studies have acknowledged the impact of weather changes on retail uncertainty. They primarily focus on understanding how weather conditions affect offline consumer behavior and aim to develop effective marketing strategies. However, there is little research on the complex impact of weather on online shopping behavior. To bridge this gap, we conduct a study with a sample of 261 consumers from China with shopping experience in community retail shops (CRSs). We utilize the S-O-R model and theories, including meteorological emotional effect theory, emotional coherence, and meteorological psychology, to model and elucidate the relationship between weather and consumers’ online shopping behavior in CRS. Our findings reveal that weather conditions affect consumers’ spending patterns and purchase diversity, mediated by consumers’ emotions and risk aversion when they comfortably shop online at home. Furthermore, employing the fsQCA model, we identify the critical path through which weather conditions and consumer types influence risk-aversion awareness. The results provide management implications for retailers to develop online marketing strategies for different consumer types. Full article

The COVID-19 pandemic changed people’s dining habits and led to the rapid rise of food delivery platforms. Ordering food online and picking it up offline has become an essential dining habit. We applied the stimulus–organism–response model and constructed a model based on factors influencing consumers’ continuous use intention from three aspects: store product quality, delivery personnel quality, and delivery platform quality. Through snowball sampling, 321 questionnaires were distributed and collected from consumers who used food delivery platforms in Taiwan. All effective questionnaires were analyzed by structural equation modeling with SPSS 18 and Amos 21. The results showed that (1) the S-O-R theory explained consumer behavior effectively. (2) Store product quality influenced store repurchase intention. (3) Delivery personnel quality and platform quality influenced a platform’s continuous usage. (4) Product quality and delivery personnel quality were key factors that influenced store repurchase intention. (5) Platform quality was an important factor that affected platform usage. Finally, recommendations were proposed based on the research findings as a reference for relevant operators in the food delivery platform industry and future researchers. Full article

Underwater methane (CH₄) detection technology is of great significance to the leakage monitoring and location of marine natural gas transportation pipelines, the exploration of submarine hydrothermal activity, and the monitoring of submarine volcanic activity. In order to improve the safety of underwater CH₄ detection mission, it is necessary to study the effect of hydrogen sulfide (H₂S) in leaking CH₄ gas on sensor performance and harmful influence, so as to evaluate the health status and life prediction of underwater CH₄ sensor arrays. In the process of detecting CH₄, the accuracy decreases when H₂S is found in the ocean water. In this study, we proposed an explainable sorted-sparse (ESS) transformer model for concentration interval detection under industrial conditions. The time complexity was decreased to O (n log_n) using an explainable sorted-sparse block. Additionally, we proposed the Ocean X generative pre-trained transformer (GPT) model to achieve the online monitoring of the health of the sensors. The ESS transformer model was embedded in the Ocean X GPT model. When the program satisfied the special instructions, it would jump between models, and the online-monitoring question-answering session would be completed. The accuracy of the online monitoring of system health is equal to that of the ESS transformer model. This Ocean-X-generated model can provide a lot of expert information about sensor array failures and electronic noses by text and speech alone. This model had an accuracy of 0.99, which was superior to related models, including transformer encoder (0.98) and convolutional neural networks (CNN) + support vector machine (SVM) (0.97). The Ocean X GPT model for offline question-and-answer tasks had a high mean accuracy (0.99), which was superior to the related models, including long short-term memory–auto encoder (LSTM–AE) (0.96) and GPT decoder (0.98). Full article

Online-to-offline (O2O) retailing offers unique opportunities for customizable assembled products with spare parts. Customers can browse and configure their desired product online, selecting from various components. Imperfect production, where a certain percentage of products have defects, can be amplified in the manufacturing system. Stricter carbon emission regulations put pressure on manufacturers to minimize waste. This creates a tension between discarding imperfect products, generating emissions, and potentially offering them at a discount through the O2O channel, which could raise quality concerns for consumers. In this study, an imperfect single-stage production process is examined, incorporating manufacturing–remanufacturing within a single stage for assembled products containing various spare parts. The study explores an investment scenario aimed at enhancing the environmental sustainability of the product. Additionally, two carbon emissions regulation strategies, specifically carbon cap-and-trade regulation and carbon taxation, are evaluated for their effectiveness in mitigating carbon footprints. The identification of waste, particularly in the form of defective items, is achieved through automated inspection techniques. The demand for spare parts associated with the assembled products is intricately linked to the selling prices set across diverse channels. Finally, the total profit of the manufacturing system is maximized with the optimized value of the selling prices, order quantity, backorder quantity, and investments in autonomated inspection, setup cost, and green technology. Numerical illustrations show that system profit was optimized when the defective rate followed a triangular distribution under carbon cap-and-trade regulation and when green technology investment helped to enhance retailer profit by $18.12\%$, whereas autonomated inspection increased retailer profit by $10.27\%$. Full article

Given the significant product spoilages of perishable goods transported over long distances, they are usually sold from suppliers to consumers through an offline direct channel. Sustainable suppliers can utilize the blockchain-based tracking system (BTS) to reduce product spoilages, enabling the spoilage reduction effect, and offer authentic information, triggering the premium effect. With the advent of e-commerce, they can now opt for an online direct channel, setting the online direct price as either non-different or different from the offline direct price, and have to face challenges in selecting the optimal sales mode. This paper addresses these complexities by developing a mathematical model to construct a sustainable suppliers-to-consumers pricing model, incorporating the BTS, in the perishable goods market. Our research reveals that the decision to adopt the BTS hinges on factors like the spoilage reduction effect, premium effect, production cost, and tag cost, with the premium effect outweighing the spoilage-reduction effect. The necessity of using the BTS grows with extended circulation times, where the BTS significantly reduces spoilages during transportation, fostering sustainable development. While sustainable suppliers may not always bear the tag cost independently, they can adjust their pricing strategies automatically and pass the tag cost to consumers for more profit. The BTS adoption decision does not influence the optimal sales mode selection strategy. The offline direct channel offers the highest profit for suppliers, followed by the Online to Offline (O2O) direct channel with differential pricing, and the O2O direct channel with non-differential pricing yields the lowest profit. Full article

A new sol-gel method that employs cation exchange from an aqueous metal ion solution with H⁺ ions of granulated alginic acid was developed for synthesizing high-purity Y₂O₃ nanoparticles. In this study, the cation exchange kinetics of H⁺~Y³⁺ in aqueous solution were analyzed using on-line pH technology and off-line inductively coupled plasma-atomic emission spectrometry (ICP-AES) analysis. Pseudo 2nd-order models were utilized to evaluate the parameters of the kinetics, suggesting that the concentration of H⁺~Y³⁺ involved in the cation exchange reaction was 1:1.733. Further, a comprehensive understanding of the Y-ALG calcination process was developed using thermo-gravimetric analysis, along with results obtained from differential scanning calorimetry (TGA/DSC). A detailed analysis of the XRD Rietveld refinement plots revealed that the crystallite sizes of Y₂O₃ nanoparticles were about 4 nm (500 °C) and 15 nm (800 °C), respectively. Differential pulse voltammetry (DPV) was employed to investigate the electrochemical oxidation of catechol. The oxidation peak currents of catechol at Y₂O₃ (500 °C)/GCE and Y₂O₃ (800 °C)/GCE showed two stages linear function of concentration (2.0~20.0 × 10⁻⁶ mol/L, 20.0~60.0 × 10⁻⁶ mol/L). The results indicated that the detection limits were equal to 2.4 × 10⁻⁷ mol/L (Y₂O₃ (500 °C)/GCE) and 7.8 × 10⁻⁷ mol/L (Y₂O₃ (800 °C)/GCE). The study not only provided a method to synthesize metal oxide, but also proposed a promising on-line pH model to study cation exchange kinetics. Full article

Purpose: The Ethos (Varian Medical Systems) radiotherapy device combines semi-automated anatomy detection and plan generation for cone beam computer tomography (CBCT)-based daily online adaptive radiotherapy (oART). However, CBCT offers less soft tissue contrast than magnetic resonance imaging (MRI). This work aims to present the clinical workflow of CBCT-based oART with shuttle-based offline MR guidance. Methods: From February to November 2023, 31 patients underwent radiotherapy on the Ethos (Varian, Palo Alto, CA, USA) system with machine learning (ML)-supported daily oART. Moreover, patients received weekly MRI in treatment position, which was utilized for daily plan adaptation, via a shuttle-based system. Initial and adapted treatment plans were generated using the Ethos treatment planning system. Patient clinical data, fractional session times (MRI + shuttle transport + positioning, adaptation, QA, RT delivery) and plan selection were assessed for all fractions in all patients. Results: In total, 737 oART fractions were applied and 118 MRIs for offline MR guidance were acquired. Primary sites of tumors were prostate (n = 16), lung (n = 7), cervix (n = 5), bladder (n = 1) and endometrium (n = 2). The treatment was completed in all patients. The median MRI acquisition time including shuttle transport and positioning to initiation of the Ethos adaptive session was 53.6 min (IQR 46.5–63.4). The median total treatment time without MRI was 30.7 min (IQR 24.7–39.2). Separately, median adaptation, plan QA and RT times were 24.3 min (IQR 18.6–32.2), 0.4 min (IQR 0.3–1,0) and 5.3 min (IQR 4.5–6.7), respectively. The adapted plan was chosen over the scheduled plan in 97.7% of cases. Conclusion: This study describes the first workflow to date of a CBCT-based oART combined with a shuttle-based offline approach for MR guidance. The oART duration times reported resemble the range shown by previous publications for first clinical experiences with the Ethos system. Full article

As a core component of power conversion systems, insulated gate bipolar transistor (IGBT) modules continually suffer from severe thermal damage caused by temperature swings and shear stress, resulting in fatigue failure. Bond wires falling off is one of the failure modes of IGBT modules. Given that the number of fallen-off bond wires is a significant parameter to evaluate the health status of the IGBT modules, this paper proposes an online identification model to recognize the number of fallen-off bond wires during normal operation. Firstly, a database containing datum $V_{ce,on}-T_j-I_C$ (collector–emitter on-state voltage $V_{ce,on}$, chip junction temperature $T_j$, collector current $I_C$) planes with different fallen-off bond wires is built based on an offline aging test. Secondly, a Foster network model and a special circuit are designed to measure the junction temperature $T_j$ and the collector–emitter on-state voltage $V_{ce,on}$, respectively. Thirdly, the feature points of the IGBT module represented by $V_{ce,on}$, $T_j$, and $I_C$ are given to the database to recognize the number of fallen-off bond wires according to the position of the feature points in the datum plane. The experimental results show that the proposed method can determine the fallen-off bond wires under the operation condition. Full article