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Wood stabilization and functionalization is a hot topic towards increasing the use of wood in buildings. Building construction and materials account for around 11% of the global CO2 emissions, thus there is increasing interest in using wood to replace concrete, steel, and aluminium. However, the perceived quality of wood in service decreases quickly in comparison with non-biodegradable alternatives, so aging must be delayed as much as possible through stabilization and functionalization. The question addressed in this paper is how to measure the perceived quality of wood products in service. The concept of wood quality is difficult to define, as it depends on a combination of factors such as customer satisfaction, wood fibre characteristics, products, applications, and so on. This paper proposes a definition of timber quality based on market price. By knowing the market value of a potential range of wood products, the proposed method calculates the loss of value due to developing defects caused by aging. Overall, the proposed methodology allows converting the subjective concept of aging into an objective $ value. A numeric example is presented based on the New Zealand timber grading rules. The results showed that 5.1 m by 150 mm by 50 mm softwood timber can lose up to 61% of its value as appearance grade if a single aging defect develops beyond the maximum allowed size.

The article examines the theoretical issues of the implementation of the life cycle of innovation and practical methods for assessing the loss of value of intellectual property in enterprises in the market. The method of the cost approach is disclosed, which assumes the accounting of the costs of reproduction of the assessed intellectual property in current prices, minus depreciation, as the most effective method for assessing intellectual property. Also considered are the rates of depreciation of fixed assets of industrial facilities, the coefficients of revaluation of the cost of fixed assets, depending on their depreciation. The article proposes the author’s approach to the gradation of the assessment of the lost usefulness of intellectual property in percentage and the relationship between the stages of the life cycle of an innovation and the state of the assessment of intellectual property..

The fresh product supply chain suffers from the quantity loss and quality loss due to its perishability in long-distance transportation, which affect the health of customers and the sustainable development of supply chain. Using low-cost normal temperature transportation or high-cost cold chain transportation has become a problem for transportation enterprises. This paper aims to investigate the impact of different transportation modes on the supply chain performance. The operation strategies of the supply chain are analyzed under three situations: no coordination contract, wholesale price contract, and revenue-sharing contract. Taking Zhanhua winter jujube as an example, the correctness of theoretical analysis is verified. The main findings are as follows. Supply chain participants, including consumers, can benefit from cold chain transportation. That the cost of cold chain transportation is below the threshold is the basic condition to use cold chain transportation. The retailer has the incentive to encourage the supplier to use cold chain transportation by increasing the wholesale price, but the wholesale price should be set within a certain range. The supplier has the incentive to use cold chain transportation under the revenue-sharing contract, but the revenue-sharing proportion needs to be within a certain range to ensure the retailer's profit. The revenue-sharing contract is superior to the wholesale price contract, and wholesale price contract is superior to no coordination contract.

Corruption and thefts of public assets harm a diffuse set of victims, weakens confidence in public institutions, damages the private investment climate, and threatens the foundations of the society as a whole. In developing countries with scarce public resources, the cost of corruption is an impediment to development: developing countries lose between US

The classification of brain tumors is a difficult task in the field of medical image analysis. Improving algorithms and machine learning technology helps radiologists to easily diagnose the tumor without surgical intervention. In recent years, deep learning techniques have made excellent progress in the field of medical image processing and analysis. However, there are many difficulties in classifying brain tumors using magnetic resonance imaging; first, the difficulty of brain structure and the intertwining of tissues in it; and secondly, the difficulty of classifying brain tumors due to the high density nature of the brain. We propose a differential deep convolutional neural network model (differential deep-CNN) to classify different types of brain tumor, including abnormal and normal magnetic resonance (MR) images. Using differential operators in the differential deep-CNN architecture, we derived the additional differential feature maps in the original CNN feature maps. The derivation process led to an improvement in the performance of the proposed approach in accordance with the results of the evaluation parameters used. The advantage of the differential deep-CNN model is an analysis of a pixel directional pattern of images using contrast calculations and its high ability to classify a large database of images with high accuracy and without technical problems. Therefore, the proposed approach gives an excellent overall performance. To test and train the performance of this model, we used a dataset consisting of 25,000 brain magnetic resonance imaging (MRI) images, which includes abnormal and normal images. The experimental results showed that the proposed model achieved an accuracy of 99.25%. This study demonstrates that the proposed differential deep-CNN model can be used to facilitate the automatic classification of brain tumors.

The architecture, engineering, and construction industry requires methods that link the capture of customer requirements with the continuous measurement of the value generated and the identification of value losses in the design process. A value analysis model (VAM) is proposed to measure the value creation expected by customers and to identify value losses through indexes. As points of reference, the model takes the Kano model and target costing, which is used in the building project design process. The VAM was developed under the design science research methodology, which focuses on solving practical problems by producing outputs by iteration. The resulting VAM allowed the measurement and analysis of value through desired, potential, and generated value indexes, value loss identification, and percentages of value fulfillment concerning the design stage. The VAM permits the comparison of different projects, visualization of the evolution of value generation, and identification of value losses to be eradicated. The VAM encourages constant feedback and has potential to deliver higher value, as it enables the determination of parameters that add value for different stakeholders and informs designers where to direct resources and efforts to enhance vital variables and not trivial variables.

Reducing postharvest losses offers a significant opportunity to enhance food availability without requiring extra production resources. A substantial portion of cereal grain goes to waste annually due to a lack of science-based knowledge, unconscious handling practices, suboptimal technical efficiency, and inadequate infrastructure. This article extensively reviews losses occurring during postharvest operations across various crops, examining diverse postharvest operations in different countries. Recent advancements in postharvest technology research are thoroughly discussed. The primary obstacles and challenges hindering the adoption and implementation of postharvest technologies are also explored. The appropriate postharvest technology relies on specific factors, including the kind of crops, production locales, seasons, and existing environmental and socioeconomic conditions.

Target value design (TVD) is a management approach that applies target costing in the design and construction industry. TVD enables a project environment with favorable characteristics to generate value. However, because the TVD’s primary assessment is cost, target cost can be met without necessarily achieving the project’s full value. This research applies the action research approach to implement TVD in a housing project and explores the value generation of the project using a value analysis model (VAM) to study the balance between cost and value fulfillment in the product and design process. According to the results, even though the target cost was achieved, the desired value of the project was not achieved during the project design. However, there is a tendency to increase value over time to a greater extent in the product and not so much in the process. The main contributions of this study are the possibility of comparing cost and value, identifying the emphasis of product over process and cost over value throughout the TVD project. This study enhances the literature on project value generation and maximization, offering new knowledge for a better understanding of how to conduct a value analysis in combination with costing in TVD projects.

Agricultural products are easy to deteriorate in long-distance transportation. Excessive circulation loss not only increases the cost of fresh agri-product supply chain, but also damages the safety and quantity of fresh agri-products. The value loss of fresh agri-products under different transportation modes was studied. This paper analyzes the conditions for the supplier to choose normal temperature transportation and cold chain transportation, and the influence of different transportation modes on the retailer’s decision. The value loss of fresh agri-products under different transportation modes was studied. The conditions of choosing normal temperature transportation or cold chain transportation and the influence of different transportation modes on the retailer’s decision are analyzed. It is found that when the supplier chooses cold chain transportation, the retailer and the whole supply chain can get more profits. The retailer is encouraged to make appropriate supply chain contracts with the supplier, such as the improved revenue-sharing contract or the cost-sharing contract, and the supplier is encouraged to adopt cold chain transportation mode to improve the utilization rate of cold chain transportation of fresh agri-products. Consumers’ sensitivity to freshness has a great impact on the strategies of supply chain members. The contribution of this work also includes reducing the circulation loss of agri-products and providing guidance for the operation and management of agri-products enterprises.

An independent set is a set of vertices in a graph in which no two vertices are adjacent to each other. The maximum weighted independent set is the independent set with the largest sum of weights in a weighted graph. Considering that existing methods are inefficient when computing the maximum weighted independent set, we propose a combined neighbor reduction rule and a loss value-based greedy strategy to improve the efficiency and increase the weight of the independent set. Additionally, we propose the efficient approximate algorithms for the maximum weighted independent set on dynamic graphs. We decompose the weight change problem into five cases and propose corresponding strategies for each case. Finally, we conduct experiments on 8 real-world datasets to verify the effectiveness and efficiency of the proposed methods.