Search Results (26)

Background: Nitric oxide (NO) is an important modulator of ovarian physiology, which contributes to angiogenesis, steroidogenesis, and redox control. The stable metabolites nitrate (NO₃⁻) and nitrite (NO₂⁻) may indicate real-time follicular function during IVF. Methods: In this prospective study, we included 89 women who underwent controlled ovarian stimulation. The Griess test was used to measure NO₂-NO₃ concentrations in follicular fluid collected on the day of oocyte retrieval. Non-parametric and correlation tests were used to investigate the associations between oocyte yield, maturity (MII), fertilization (2PN), embryo development, and hormone levels. Results: Higher NO₂-NO₃ levels were substantially associated with increased total oocyte count, MII oocytes (p = 0.014), and 2PN embryos (p = 0.029). This suggests a strong relationship between NO bioavailability and oocyte competence. NO₂-NO₃ levels showed a positive correlation with estradiol (p < 0.001) and progesterone (p < 0.001), suggesting a possible function in granulosa cell steroidogenesis. Conclusions: Follicular NO metabolites are candidate functional indicators for oocyte quality evaluation and intrafollicular steroidogenic activity. Their predictive value may improve customized IVF treatment, especially in individuals with complicated ovarian phenotypes such as PCOS or decreased ovarian reserve. Full article

Churn prediction has become one of the core concepts in customer relationship management within the insurances, telecom, and internet service provider industries, which is essential in customer retention. Therefore, this study attempts to analyze the effectiveness of the advanced machine learning and deep learning models for churn prediction in the evaluation of the models’ performance across different sectors. This would help conclude whether the varied patterns of the churn throughout different sectors to the level that affects the model performance and to what extent. The work includes three datasets: namely, insurance churn, internet service provider customer churn, and Telecom churn datasets. The implementation and comparison conducted in this study of models include XGBoost, Convolutional Neural Networks (CNNs), and Ensemble Deep Learning with the pre-trained hybrid approach. The results show that the ensemble deep learning model outperforms other models in terms of accuracy and F1-score, achieving accuracies of up to 95.96% in the insurance churn dataset and of 98.42% in the telecom churn dataset. Moreover, traditional machine learning models like XGBoost also produced competitive results for selected datasets. The proposed deep learning ensembles reveal the strength and possibility for churn prediction and provide a benchmark for future research relevant to customer retention strategies. Also, the proposed ensemble deep learning model shows stable performance across different sectors, which reflects its ability to capture the varied churn patterns of different sectors. Full article

Under the influence of climate change, extreme rainfall events (EREs) have become increasingly frequent. The urban waterlogging caused by these events has a particularly significant impact on cities with flat terrain and inadequate surface runoff dynamics. This study proposes a Coordinated Regulation of Storage and Discharge Mode (CRSD) tailored for plain cities. It establishes an evaluation system for CRSD based on regional rainwater flood carrying capacity, drainage capacity, and regional value, thereby assigning customized storage and drainage strategies to different urban areas. The model optimizes the relationship between storage and drainage across regions based on the fundamental principles of CRSD and establishes dynamic cross-regional water distribution rules according to optimization objectives. Finally, CRSD is validated using the MIKE models. The results indicate that as the rainfall return period increases, the area affected by urban waterlogging expands, though the proportion of waterlogging across various severity levels remains stable. CRSD can effectively alleviate urban waterlogging caused by EREs, with waterlogging reduction percentages ranging from 12.21% to 18.50%. Among the optimization schemes, Safe Consumption (SC) delivers the best overall performance, reducing waterlogging by up to 1.80 km² under 500 yr. The Average Pressure (AP) performs best in high-value areas, reducing waterlogging by up to 1.96 km² under the same return period. This study advances urban flood management by integrating cross-regional coordination mechanisms with blue–green–grey infrastructure, providing a replicable strategy for flatland cities to cope with the increasing challenges of EREs. Full article

Three-dimensional (3D) printing attracts significant interest in the food industry for its ability to create complex structures and customize nutritional content. Printing materials, or inks, are specially formulated for food or nutraceuticals. These inks must exhibit proper rheological properties to flow smoothly during printing and form stable final structures. This study evaluates the relationship between rheological properties and printability in phytosterol-enriched monoglyceride (MG) oleogel-based inks, intended for nutraceutical applications. Key rheological factors, including gelation temperature (Tg), elastic (G′) and viscous (G″) modulus, and viscosity (µ) behavior with shear rate ($\dot{\gamma }$), were analyzed for their impact on flow behavior and post-extrusion stability. Furthermore, this study allowed the development of an operation map to predict successful printing based on material µ and Tg. Oleogels (OGs) were prepared with high-oleic sunflower oil (HOSO) and 10 wt% MG, enriched with phytosterols (PSs) at concentrations between 0 and 40 wt%. While higher PS content generally led to an increase in both Tg and µ, the 10 wt% PS mixture exhibited a different behavior, showing lower Tg and µ compared to the 0 wt% and 5 wt% PS mixtures. The optimal PS concentration was identified as 20 wt%, which exhibited optimal properties for 3D printing, with a Tg of 78.37 °C and µ values ranging from 0.013 to 0.032 Pa.s that yielded excellent flowability and adequate G′ (3.07 × 10⁶ Pa) at room temperature for self-supporting capability. These characteristics, visualized on the operational map, suggest that 20% PS OGs meet ideal criteria for successful extrusion and layered deposition in 3D printing. Full article

Continuous advancements in technology have made it possible to integrate clear aligner therapy (CAT) with orthognathic surgery. This case report presents a novel, individually-planned workflow, combining CAT with a surgery-first orthognathic approach (SFOA) in collaborating with engineers for an in-house production of surgical guides and customized titanium plates. The patient was evaluated subjectively, using the Oral Health-Related Quality of Life-14 (OHIP-14) questionnaire and Orthognathic Quality of Life questionnaire (OQLQ), and objectively with the Peer Assessment Rating (PAR) index. The patient displayed the planned occlusal relationship with no report of discomfort in the temporomandibular joint (TMJ) or post-surgical complications. The surgical and occlusal outcomes have remained consistent and stable after debonding. A decreased score was reported in both questionnaires and the PAR after treatment, thereby indicating improvements in both subjective and objective evaluations. This case report demonstrates that with proper individual planning, satisfactory subjective and objective outcomes can be achieved when combining SFOA with CAT. Full article

Stroke often causes neuromotor disabilities, impacting index finger function in daily activities. Due to the role of repetitive, even passive, finger movements in neuromuscular re-education and spasticity control, this study aims to design a rehabilitation exoskeleton based on the pulp pinch movement. The exoskeleton uses an underactuated RML topology with a single degree of mobility, customized from 3D scans of the patient’s hand. It consists of eight links, incorporating two consecutive four-bar mechanisms and the third inversion of a crank–slider. A two-stage genetic optimization was applied, first to the location of the intermediate joint between the two four-bar mechanisms and later to the remaining dimensions. A targeted genetic optimization process monitored two quality metrics: average mechanical advantage from extension to flexion, and its variability. By analyzing the relationship between these metrics and key parameters at different synthesis stages, the population evaluated is reduced by up to 96.2%, compared to previous studies for the same problem. This custom-fit exoskeleton uses a small linear actuator to deliver a stable 12.45 N force to the fingertip with near-constant mechanical advantage during flexion. It enables repetitive pulp pinch movements in a flaccid finger, improving rehabilitation consistency and facilitating home-based therapy. Full article

Supply chain security plays a critical role in ensuring the stable and continuous operation of society. Moreover, enhancing the quality of export products is crucial for improving environmental sustainability, as it helps reduce waste emissions and other related factors. Therefore, this paper employs data from Chinese A-share-listed companies and customs data from 2001 to 2015 to investigate this relationship. The main findings are as follows: (i) The supply chain concentration negatively impacts the quality of export products, a finding that remains robust after testing. (ii) In some firms, such as those where top executives possess digital-related expertise, the adverse effects of the supply chain concentration are likely mitigated. (iii) The channels through which the supply chain concentration affects export product quality may include firm size, productivity, and supply chain efficiency. (iv) Enhancements in infrastructure resilience, firm structure resilience, and industrial structure resilience through investments in regional fixed assets, overseas subsidiaries, and advancements in industrial structure, respectively, are likely to mitigate the negative impacts of the supply chain concentration. These conclusions may hold significant value for promoting both societal and environmental sustainability. Full article

Subscription services have become popular in recent years, breaking the traditional business model of one-time payment and prompting operators to build long-term loyal relationships with their customers. As smartphones are popular in Taiwan and the Taiwanese have a high acceptance of new technologies, is it possible for domestic restaurants to reach a win-win situation for both consumers and restaurant operators and to reduce food waste through subscription services? The Technology Acceptance Model was used in this study to explore consumers’ perceived usefulness, perceived ease of use, and attitudes toward restaurant subscription platforms, with two variables, new environmental paradigm and environmental behavior, added to probe the relations with intention to use. This study was conducted by convenience and snowball sampling, and the subjects were consumers eating out. A total of 400 questionnaires were collected and 369 valid ones were returned, with a response rate of 92.25%. The results show that perceived usefulness, perceived ease of use, new environmental paradigm, environmental behaviors, and attitude toward using have significant positive effects, and attitude toward using has the same effect on intention to use. In addition, attitude toward using has a mediating effect on perceived usefulness, new environmental paradigm, environmental behavior, and intention to use. Finally, it is expected that the results of this study can be used as a reference for restaurant operators to adopt subscription services in order to build long-term and stable relationships with consumers. Furthermore, new entrepreneurs can also evaluate the feasibility of building a subscription platform like this one, which can provide a convenient and economical option for consumers dining out, as well as reduce food waste. Full article

Nowadays, the focus of flow shops is the adoption of customized demand in the context of service-oriented manufacturing. Since production tasks are often characterized by multi-variety, low volume, and a short lead time, it becomes an indispensable factor to include supporting logistics in practical scheduling decisions to reflect the frequent transport of jobs between resources. Motivated by the above background, a hybrid method based on dual back propagation (BP) neural networks is proposed to meet the real-time scheduling requirements with the aim of integrating production and transport activities. First, according to different resource attributes, the hierarchical structure of a flow shop is divided into three layers, respectively: the operation task layer, the job logistics layer, and the production resource layer. Based on the process logic relationships between intra-layer and inter-layer elements, an operation task–logistics–resource supernetwork model is established. Secondly, a dual BP neural network scheduling algorithm is designed for determining an operations sequence involving the transport time. The neural network 1 is used for the initial classification of operation tasks’ priority; and the neural network 2 is used for the sorting of conflicting tasks in the same priority, which can effectively reduce the amount of computational time and dramatically accelerate the solution speed. Finally, the effectiveness of the proposed method is verified by comparing the completion time and computational time for different examples. The numerical simulation results show that with the increase in problem scale, the solution ability of the traditional method gradually deteriorates, while the dual BP neural network has a stable performance and fast computational time. Full article

In previous research on the development of the relationships between product attributes and customer satisfaction, the models did not adequately consider nonlinearity and the fuzzy emotions of customers in online reviews. Also, stable customer satisfaction was considered. However, customer satisfaction is changing with time rapidly, and a time-series analysis for customer satisfaction has not been conducted previously. To address these challenges, this study designed a novel methodology using adaptive neuro-fuzzy inference systems (ANFIS) in conjunction with Bi-objective particle swarm optimization (BOPSO) and sentiment analysis techniques. Sentiment analysis is employed to extract time-series customer satisfaction data from online reviews. Then, an ANFIS with the BOPSO method is proposed for the establishment of customer satisfaction models. In previous studies, ANFIS is an effective method to model customer satisfaction which can handle fuzziness and nonlinearity. However, when dealing with a large number of inputs, the modeling process may fail due to the complexity of the structure and the lengthy computational time required. Incorporating the BOPSO algorithm into ANFIS can identify the optimal inputs in ANFIS and effectively mitigate the inherent limitations of ANFIS. Using mobile phones as a case study, a comparison was performed between the proposed approach and another four approaches in modeling time-series customer satisfaction. Full article

Under the background of the “dual carbon” targets and continuously promoted power system reform, the application of a high proportion of renewable energy is becoming increasingly widespread. All sectors of society have greater demands for more appropriate electricity sales packages to guide the behavior of power users, which will in turn help conserve energy, reduce emissions, and finally achieve low-carbon operation of the power market economy. However, the existing methods of recommending electricity sales packages fail to provide appropriate and accurate recommendations for the users lacking preference information. Therefore, this paper proposes a two-sided matching decision-making method of an electricity sales package based on disappointment theory. First of all, according to the incomplete fuzzy preference relationship provided by the power user and the electricity sales package, the respective priority weight vector is calculated, and then the subjective satisfaction matrix of the power user and the electricity sales package is calculated. Next, the adjusted satisfaction matrix is calculated by adding the influence of the theory of elation and disappointment. Then, on the basis of the adjusted satisfaction matrix, an optimization model aiming at maximizing the total satisfaction of electric power customers and electricity sales packages is established, and the optimal stable matching model of electric power customers and electricity sales packages is obtained. Lastly, taking an industrial park in Zhejiang Province as an example, using the bilateral matching method proposed in this article, the optimal matching schemes for five electric power customers and six electricity sales packages is obtained, which shows the effectiveness and rationality of the two-sided matching decision-making method of electricity sales packages based on the disappointment theory. Full article

This paper is oriented toward the specific testing of polymer composites and textile PA66 cords used as reinforcement for composites. The aim of the research is to validate the proposed new testing methods for low-cyclic testing of polymer composites and PA66 cords for the characterization of material parameters useful as input data for computational tire simulations. Part of the research is the design of experimental methods for polymer composites and test parameters such as load rate, preload, and other parameters such as strain for the start and stop of cycle steps. The DIN 53835-13 standard is used for the conditions of textile cord during the first five cycles. A cyclic load is carried out at two temperatures of 20 °C and 120 °C. The testing method includes a hold step for 60 s between each loop. The video-extensometer technique is used for testing. The paper evaluated the effect of temperatures on the material properties of PA66 cords. The true stress-strain (elongation) dependences between points for the video-extensometer of the fifth cycle of every cycle loop are the data results from composite tests. The forcestrain dependences between points for the video-extensometer are the data results from tests of the PA66 cord. These dependencies can be used as input material data of textile cords in the computational simulation of tire casings using a custom material model definition. The fourth cycle in every cycle loop of polymer composites can be considered a stable cycle because the change in the maximum true stress between the fourth and fifth cycles is 1.6%. Other results of this research include a relationship between stress and the number of cycle loops as the second-degree polynomial curve for polymer composites and a simple relationship to describe the value of the force at each end of the cycles for a textile cord. Full article

Sustainable development integrates business, environmental, and social objectives into a unified effort to achieve a common goal. Sustainable customer relationship management (CRM) combines company strategy, customer-focused business processes, and computer technologies. From the consumer’s perspective, it lowers psychological, energy, time, and other costs; from the company’s perspective, it offers a means of engaging with customers to build lasting and reliable relationships. The sustainable CRM program provides advantages to businesses in various industries, particularly online commerce. It alludes to a comprehensive strategy that promotes solid interactions between buyers and sellers of goods and services. Since current customer retention is less costly than new customer attraction in competitive markets, especially online shopping, identifying the factors affecting relationship management with stable customers is essential. This investigation intends to evaluate the effect of the use of management information systems (MIS), as well as insights on employee behavior and knowledge, and customer behavior (satisfaction and loyalty), on the effectiveness of sustainable CRM in online shopping. The model is validated using the PLS–SEM technique, and study sample of 293 employees and managers from private organizations. According to the results, the MIS, employee behavior and knowledge, customer satisfaction, and customer loyalty influence the effectiveness of sustainable CRM in online shopping. Furthermore, employee behavior and knowledge positively moderate the relationship between customer loyalty and the effectiveness of sustainable CRM. However, the moderating role of employee behavior and knowledge on customer satisfaction and the effectiveness of sustainable CRM is not confirmed. Overall, taking these characteristics into account might help organizations to take significant steps toward increasing the efficacy of sustainable CRM. Full article

Total hip arthroplasty is a widely performed operation allowing disabled patients to improve their quality of life to a degree greater than any other elective procedure. Planning for a THA requires adequate patient assessment and preoperative characterizations of acetabular bone loss via radiographs and specific classification schemes. Some surgeons may be inclined to ream at a larger diameter thinking it would lead to a more stable press-fit, but this could be detrimental to the acetabular wall, leading to intraoperative fracture. In the attempt to reduce the incidence of intraoperative fractures, the current study aims to identify how increased reaming diameter degrades and weakens the acetabular rim strength. We hypothesized that there is proportionality between the reaming diameter and the reduction in acetabular strength. To test this hypothesis, this study used bone surrogates, templated from CT scans, and reamed at different diameters. The obtained bone surrogate models were then tested using an Intron 8874 mechanical testing machine (Instron, Norwood, MA) equipped with a custom-made fixture. Analysis of variance (ANOVA) was used to identify differences among reamed diameters while linear regression was used to identify the relationship between reamed diameters and acetabular strength. We found a moderate correlation between increasing reaming diameter that induced thinning of the acetabular wall and radial load damage. For the simplified acetabular model used in this study, it supported our hypothesis and is a promising first attempt in providing quantitative data for acetabular weakening induced by reaming. Full article

Customer segmentation has been a hot topic for decades, and the competition among businesses makes it more challenging. The recently introduced Recency, Frequency, Monetary, and Time (RFMT) model used an agglomerative algorithm for segmentation and a dendrogram for clustering, which solved the problem. However, there is still room for a single algorithm to analyze the data’s characteristics. The proposed novel approach model RFMT analyzed Pakistan’s largest e-commerce dataset by introducing k-means, Gaussian, and Density-Based Spatial Clustering of Applications with Noise (DBSCAN) beside agglomerative algorithms for segmentation. The cluster is determined through different cluster factor analysis methods, i.e., elbow, dendrogram, silhouette, Calinsky–Harabasz, Davies–Bouldin, and Dunn index. They finally elected a stable and distinctive cluster using the state-of-the-art majority voting (mode version) technique, which resulted in three different clusters. Besides all the segmentation, i.e., product categories, year-wise, fiscal year-wise, and month-wise, the approach also includes the transaction status and seasons-wise segmentation. This segmentation will help the retailer improve customer relationships, implement good strategies, and improve targeted marketing. Full article