Laozi’s Ming (name), Qi (tangible part) and Dao (intangible part), coexisting in the same substance, can be compared with Heidegger’s triad existences: Seiende (being), Dasein (beings) and Sein (to be). In Laozi, Dao is the essential metonymy for the existence of things from Wu (void, nothing) to You (there is, reality). The effect of Dao is De (virtue) and the combined term of them is Dao-De (morality). By conceptual blend theory, we may draw the following conclusion from the perspective of Heidegger’s ontology of triad existences and Laozi’s Dao with its companions: any being (Seiende or Ming) exists in the form of combination beings (Dasein or Qi) and to be (Sein or Dao). According to Proper Parts Principle, if z, x, y is used to represent being, beings and to be respectively, then, the expression of all things will be the form: z∃ (x) ⊕ y. In terms of independent concept and function, Dao exists as whole. While from Laozi’s triangular relationship among Ming, Dao and Qi, Dao can be considered as a proper parthood, too. Both Laozi and Heidegger emphasized that existence is changing, but Heidegger attributed the reason for change to time, while Laozi to Dao. Dao can be considered as way, essence, nothingness, empty, void etc. in structure, but it doesn’t mean it’s zero or none-existing. On the contrary, it is a form of existence from exotic domain. Both the numeric expression of Heidegger’s triad existences and Laozi’s triangle existences of Dao with its companions can be written as "z∃x (1) ⊕ y(Ø) Û z{1, Ø}. In which, Ø is empty set as Laozi’s Dao or Heidegger’s Sein (Ø Û 0).

Realistic project scheduling and control are critical for running a profitable enterprise in the construction industry. Finance-based scheduling aims to produce more realistic schedules by considering both resource and cash constraints. Since the introduction of finance-based scheduling, its literature has evolved from a single-objective model to a multi-objective model and also from a single-project problem to a multi-project problem for a contractor. This study investigates the possibility of cooperation among contractors with concurrent projects to minimize financial costs. Contractors often do not use their entire credit and may be required to pay a penalty for the unused portions. Therefore, contractors are willing to share these unused portions to decrease their financing costs and consequently improve their overall profits. This study focuses on the partnering of two contractors in a joint finance-based scheduling where contractors are allowed to lend credit to or borrow credit from each other at an internal interest rate. We apply this approach to an illustrative example in which two concurrent projects have the potential for partnering. Results show that joint finance-based scheduling reduces the financing cost for both contractors and leads to additional overall profits. Our further analyses highlight the intricate dynamics impacting additional net profit, revealing optimal scenarios for cooperation in complex project networks.

Finding the right technique to optimize a complex problem is not an easy task. There are hundreds of methods, especially in the field of metaheuristics suitable for solving NP-hard problems. Most metaheuristic research is characterized by developing a new algorithm for a task, modifying or improving an existing technique. The overall rate of reuse of metaheuristics is small. Many problems in the field of logistics are complex and NP-hard, so metaheuristics can adequately solve them. The purpose of this paper is to promote more frequent reuse of algorithms in the field of logistics. For this, a framework is presented, where tasks are analyzed and categorized in a new way in terms of variables or based on the type of task. A lot of emphasis is placed on whether the nature of a task is discrete or continuous. Metaheuristics are also analyzed from a new approach: the focus of the study is that, based on literature, an algorithm has already effectively solved mostly discrete or continuous problems. An algorithm is not modified and adapted to a problem, but methods that provide a possible good solution for a task type are collected. A kind of reverse optimization is presented, which can help the reuse and industrial application of metaheuristics. The paper also contributes to providing proof of the difficulties in the applicability of metaheuristics. The revealed research difficulties can help improve the quality of the field and, by initiating many additional research questions, it can improve the real application of metaheuristic algorithms to specific problems. The paper helps with decision support in logistics in the selection of applied optimization methods. We tested the effectiveness of the selection method on a specific task, and it was proven that the functional structure can help the decision when choosing the appropriate algorithm.

The profound impact of China's concept of healthy development on various fields of society has influenced the mode of university education, and has gradually undergone changes in actual teaching modes, ways of thinking, and technologies. As one of the important educational courses in universities and sports departments, the reasonable introduction and implementation of functional training models in practical guidance can deepen students' learning of basic dance and skills, and further improve the performance of the dance stage. As a mentor, teachers should play the role of functional guidance essentials based on students' differentiated training abilities, optimize educational content from students' physical function training, and make adjustments. The professional functional training method is adopted to establish the practical application and promotion of functional training in university physical education.

This study evaluated the performance of several machine learning classifiers—Decision Tree, Random Forest, Logistic Regression, Gradient Boosting, SVM, KNN, and Naive Bayes—for adaptability classification in online and onsite learning environments. Decision Tree and Random Forest models achieved the highest accuracy of 0.833, with balanced precision, recall, and F1-scores, indicating strong, overall performance. In contrast, Naive Bayes, while having the lowest accuracy (0.625), exhibited high recall, making it potentially useful for identifying adaptable students despite lower precision. SHAP (SHapley Additive exPlanations) analysis further identified the most influential features on adaptability classification. IT Resources at the University emerged as the primary factor affecting adaptability, followed by Digital Tools Exposure and Class Scheduling Flexibility. Additionally, Psychological Readiness for Change and Technical Support Availability were impactful, underscoring their importance in engaging students in online learning. These findings illustrate the significance of IT infrastructure and flexible scheduling in fostering adaptability, with implications for enhancing online learning experiences.

The quality of preschool education is related to the stability of the early childhood teaching force. With the help of qualitative research methods, the study analyzed the data of eight teachers who left the profession and explored the process of teachers leaving the profession, and found that the encounter between "settling down" and "professional feelings", the struggle for transformation between "professional feelings" and "the situation", and the struggle for transformation between "settling down" and "the situation" are all related to the stability of the early childhood education workforce. It was found that the encounter and tug-of-war between "settling down" and "professional feelings", the struggle for transformation between "professional feelings" and "the situation", and the rational weighing between "settling down" and "the situation" are the important factors affecting the departure from the profession. The essence is the tension between "teachers as human beings" and "human beings as teachers". Therefore, it is necessary to pay attention to the unity of "person" and "teacher", and to alleviate the problem of teachers leaving the organization by creating a fair, democratic and professional working atmosphere and strengthening the awareness of professional education.