Search Results (11)

Background/Objectives: The formation of oral biofilms in periodontal pockets and around dental implants with induction of periodontitis or peri-implantitis is an increasing problem in dental health. The intelligent design of a biofilm makes the bacteria embedded in the biofilm matrix highly tolerant to antiseptic therapy, often resulting in tooth or implant loss. The question therefore arises as to which mouthwashes have eradication potential against oral biofilm. Methods: A human oral biofilm model was developed based on donated blood plasma combined with buffy coats, inoculated with oral pathogenic bacterial species found in periodontal disease (Actinomyces naeslundii, Fusobacterium nucleatum, Streptococcus mitis, and Porphyromonas gingivalis). Over a span of 7 days, we tested different mouth rinsing and antiseptic solutions (Chlorhexidine, Listerine^®, NaOCl, Octenisept^®, and Octenident^®) covering the matured biofilm with 24 h renewal. Phosphate-buffered saline (PBS) was used as a control. Bacterial growth patterns were detected via quantitative polymerase chain reaction (qPCR) after 2, 4, and 7 days of treatment. Results: While all groups showed initial bacterial reduction, the control group demonstrated strong regrowth from day 2 to 4. Listerine showed a near-significant trend toward bacterial suppression. Additionally, strain-specific efficacy was observed, with Octenisept^® being most effective against Streptococcus mitis, Octenident^® and NaOCl showing superior suppression of Actinomyces naeslundii, and Listerine^® outperforming other solutions in reducing Fusobacterium nucleatum. Donor-specific, individual variability further influenced treatment outcomes, with distinct trends in bacterial suppression and regrowth observed across donors. Conclusions: These findings underscore the complexity of biofilm-associated infections and highlight the importance of targeted therapeutic approaches for managing bacterial biofilms. In this experiment, the donor-specific outcomes of the antimicrobial effects of the solutions may indicate that genetic predisposition/tolerance to oral infections appears to play a critical role in the control of oral biofilms. Full article

This study aims to assess and analyze the urban food resilience of the Zhengzhou metropolitan area, proposing innovative assessment frameworks and methodologies. Utilizing a dual-level analysis approach that combines long-term planning impact analysis (2000–2020) with short-term resilience assessment (2018–2022), the study integrates public government data and Geographic Information System (GIS) data, employing spatial analysis, Analytic Hierarchy Process (AHP), and fuzzy comprehensive evaluation techniques. Findings from 2000 to 2020 indicate that urban planning within the metropolitan area has significantly impacted the food system. Urbanization has led to reduced agricultural land, but improvements in infrastructure have enhanced the efficiency of the food supply chain. Woodland and grassland areas have remained relatively stable, providing an ecological buffer for the food system. Building on this, the short-term assessment from 2018 to 2022 reveals significant dynamic changes and a continuous improvement trend in food resilience, though there is still room for enhancement. Food supply chain management and emergency preparedness and management contributed the most to overall resilience. Notably, extreme events such as the COVID-19 pandemic and the “7.20 Flood Disaster” prompted the adoption of innovative measures to enhance food resilience. The study develops a multidimensional theoretical framework and assessment system for urban food resilience, offering new perspectives and methods for understanding and enhancing urban food resilience. The results highlight the critical role of urban planning in enhancing food resilience, recommending the integration of the food system into comprehensive urban planning, strengthening regional collaboration, and enhancing public engagement. These findings provide an important basis for policymaking and practice aimed at improving the long-term adaptability and short-term recovery capabilities of urban food systems. Full article

The complexity of construction in prefabricated buildings makes it vulnerable to uncertainty in project timelines, and traditional project timeline management is insufficient to control project timelines for prefabricated buildings. Therefore, research on project timeline management for prefabricated buildings is needed in order to optimize project timelines and improve project execution rates. This study proposed an improved method of setting prefabricated building buffer zones through the use of improved grey critical chain technology. Five major factors affecting project timelines in actual prefabricated construction projects were selected: personnel experience, degree of prefabrication, technical complexity, reasonableness of construction plans, and degree of construction space availability. The OPA technique was introduced and combined with the entropy weight method to improve the comprehensive weight coefficient of the grey critical chain calculation of the factors affecting the timeline. Other influencing coefficients were determined, and a new calculation method for the size of prefabricated building buffer zones was proposed. Monte Carlo simulations were conducted in Matlab on actual construction projects to ensure the scientific rationality of the improved method. The results showed that compared with the classical buffer calculation methods (cut-and-paste method, C&PM and square root standard deviation method, RSEM), the project timeline was reduced by 14.3% and 11.7%, respectively, using the improved method. The improved method not only reduces project uncertainties, but also achieves the goal of optimizing project timelines, and it is reasonable and effective. The results of the study provide a direction for the project timeline management of prefabricated building critical chains, and this method can be applied to the planning and management of prefabricated building buffer zones. Full article

Industrial projects are plagued by uncertainties, often resulting in both time and cost overruns. This research introduces an innovative approach, employing Reinforcement Learning (RL), to address three distinct project management challenges within a setting of uncertain activity durations. The primary objective is to identify stable baseline schedules. The first challenge encompasses the multimode lean project management problem, wherein the goal is to maximize a project’s value function while adhering to both due date and budget chance constraints. The second challenge involves the chance-constrained critical chain buffer management problem in a multimode context. Here, the aim is to minimize the project delivery date while considering resource constraints and duration-chance constraints. The third challenge revolves around striking a balance between the project value and its net present value (NPV) within a resource-constrained multimode environment. To tackle these three challenges, we devised mathematical programming models, some of which were solved optimally. Additionally, we developed competitive RL-based algorithms and verified their performance against established benchmarks. Our RL algorithms consistently generated schedules that compared favorably with the benchmarks, leading to higher project values and NPVs and shorter schedules while staying within the stakeholders’ risk thresholds. The potential beneficiaries of this research are project managers and decision-makers who can use this approach to generate an efficient frontier of optimal project plans. Full article

In order to solve the problems such as project duration delay caused by unreasonable buffer zone setting, a critical chain buffer zone setting method is proposed based on fragility theory. Firstly, we propose that the construction process is brittle and the brittleness of the construction process was analyzed. Secondly, this paper introduces a risk-integrated impact rate to describe the uncertainty of the construction process and establishes a brittle risk entropy function. Then, it presents entropy models and modification models of project buffers and feeding buffers based on the original Root Square Error Method. Finally, an engineering project was selected as an example, and the simulation was carried out using the Monte Carlo simulation software Crystal Ball, and the resulting method was compared with three buffer zone calculation methods. The results show that the method can effectively reduce the construction period and is effective and practical when compared to the other three buffer calculation methods. The results of the study provide a new way of thinking about buffer settings based on existing critical chain project management methods. Full article

Numerous constraints affect construction projects, and lack of management may lead to schedule deviation. In the execution phase of the project, due to the lack of timely access to the required resources and the existence of uncertainty, the project activities do not progress following the schedule, and as a result, schedule deviation occurs. The scheduling addresses resource constraints by the critical chain method and deals with delays in activities by placing buffers that have emerged as a method for scheduling construction projects. This paper presents a new bi-objective mathematical model which aims to reduce delay and increase quality, based on the critical chain method and resource constraint for scheduling construction projects. In the proposed model, the activities have been considered multi-mode ones. Moreover, this paper has assumed each activity to be executed in a normal or crashing way. Due to the uncertainty in real-world problems, the duration of the activity is expressed using triangular interval-valued fuzzy numbers. A new interval-valued fuzzy solution process is presented in this paper using a two-step approach. First, the equivalent crisp model is given; then in the second step, a goal programming approach is applied for transforming the bi-objective model into the single-objective one. Finally, the mathematical model is implemented on a case study adapted from the literature, and sensitivity analysis of the results is conducted. Full article

This study concerns the use of the critical chain method to schedule the construction of renewable energy facilities. The critical chain method is recognized as a useful project management tool, transforming a stochastic problem of uncertainty in activity durations into a deterministic one. However, this method has some shortcomings. There are no clear principles of grouping non-critical activities into feeding chains. Another ambiguity is sizing the feeding buffers with regard to the topology of the network model and the resulting dependencies between activities, located in different chains. As a result, it is often necessary to arbitrarily adjust the calculated sizes of feeding buffers before inserting them into the schedule. The authors present the new approach to sizing the time buffers in the schedule, enabling a quick assessment of the quality of a given solution variant and finding a solution that best meets the established criteria, conditions, and constraints. The essence of the presented approach is the two-step sizing of time buffers with the use of deterministic optimization and stochastic optimization techniques. Taking into account construction management needs, the optimization criteria are based on the construction project cash flow analysis. The effectiveness of the presented approach is illustrated by an example of developing a wind power plant construction schedule. According to the results, the presented approach ensures the protection of the scheduled completion date of the construction and the stability of the schedule. Full article

In order to overcome the difficulty in quantifying rework by traditional project schedule management tools, this study proposes an innovative method, namely improved Critical Chain Design Structure Matrix (ICCDSM). From the perspective of information flow, the authors firstly make assumptions on activity parameters and interactions between activities. After that, a genetic algorithm is employed to reorder the activity sequence, and a banding algorithm with consideration of resource constraints is used to identify concurrent activities. Then potential criticality is proposed to measure the importance of each activity, and the rework impact area is implicated to indicate potential rework windows. Next, two methods for calculating project buffer are employed. A simulation methodology is used to verify the proposed method. The simulation results illustrate that the ICCDSM method is capable of quantifying and visualizing rework and its impact, decreases iterations, and improves the completion probability. In this vein, this study provides a novel framework for rework management, which offers some insights for researchers and managers. Full article

Engineering, Procurement, and Construction (EPC) of oil and gas megaprojects often experience cost overruns due to substantial schedule delays. One of the greatest causes of these overruns is the mismanagement of the project schedule, with the piping works (prefabrication and installation) occupying a majority of that schedule. As such, an effective methodology for scheduling, planning, and controlling of piping activities is essential for project success. To meet this need, this study used the Critical Chain Project Management (CCPM) to develop a piping construction delay prevention methodology, incorporating material procurement processes for EPC megaprojects. Recent studies indicate that the traditional scheduling method used on oil and gas mega projects has critical limitations regarding resource scarcity, calculation of activity duration, and dealing with uncertainties. To overcome these limitations, the Theory of Constraints-based CCPM was proposed and implemented to provide schedule buffers management. Nonexistent in literature, and of critical importance, is this paper’s focus on the resource buffer, representing material uncertainty and management. Furthermore, this paper presents a step-by-step process and flow chart for project, construction, and material managers to effectively manage a resource buffer through the CCPM process. This study extends the knowledge of traditional resource buffers in CCPM to improve material and procurement management, thus avoiding the shortage of piping materials and minimizing delays. The resultant process was validated by both deterministic and probabilistic schedule analysis through two case studies of a crude pump unit and propylene compressor installation at a Middle Eastern Refinery Plant Installation. The results show that the CCPM method effectively handles uncertainty, reducing the duration of piping works construction by about a 35% when compared to the traditional method. Furthermore, the results show that, in not considering material uncertainty (resource buffers), projects schedules have the potential for approximately a 5% schedule growth with the accompanying delay charges. The findings have far-reaching applications for both oil and gas and other sectors. This CCPM case-study exemplifies that the material management method represents an opportunity for industry to administrate pipeline installation projects more effectively, eliminate project duration extension, develop schedule-based risk mitigation measures pre-construction, and enable project teams to efficiently manage limited human and material resources. Full article

The lack of integrated project control techniques covering both qualitative and quantitative indices is one of the most important reasons leading to unfinished projects under predetermined schedules and expected budgets. Two modern techniques proposed in project control—the critical chain method and buffer management (CCM/BM), and the earned value analysis or earned value management and earned schedule (EVM/ES)—both have advantages and disadvantages. Goldratt proposed the CCM/BM method in 1997 based on the theory of constraint (TOC), but this method was not successful despite some improvements in project control because of some executive reasons. The most noteworthy constraint of this method is the management of time and time risks (use of a time buffer) of the project more than the subject. Goldratt believed that time control could be the most critical issue in project control. In other words, the overall problems associated with each project can be solved as long as the buffer time is under control and there is no need to control the other items. EVM/ES is one of the important techniques used to calculate real project development; it has been used for the integrated management of sustainable projects in recent decades. Using this technique, project managers can predict the final status of the project in terms of the necessary time and cost to finish the project. However, this method is limited by the management of the project cost and the lack of interference in the project risks. In sum, the CCM/BM method focuses on time and its risks associated with the project, thus making it advantageous to other techniques. Conversely, EVM/ES focuses on the costs or schedule with non-probabilistic assumptions, giving some interesting results. Therefore, this study aims to represent an integrated framework that considers the advantages of both CCM/BM and EVM/ES, called the efficiency–risk approach, which is implemented to control sustainable projects efficiently. This hybrid form can simultaneously control all the parameters, including both quantitative and qualitative variables, time, cost, and risk in conjunction with the project. Schedule and cost buffers of the project are derived using new formulations that provide appropriate estimations on the duration and cost for completing the sustainable projects and the relevant risks. The proposed ideas are analyzed and described through an industrial case study in the Steel Company, Isfahan, Iran. Full article

Exploiting the Bachet weight decomposition theorem, a new two-dimensional filter is designed. The filter can be adapted to different multimedia applications, but in this work it is specifically targeted to image processing applications. The method allows emulating standard 32 bit floating point multipliers using a chain of fixed point adders and a logic unit to manage the exponent, in order to obtain IEEE-754 compliant results. The proposed design allows more compact implementation of a floating point filtering architecture when a fixed set of coefficients and a fixed range of input values are used. The elaboration of the data proceeds in raster-scan order and is capable of directly processing the data coming from the acquisition source thanks to a careful organization of the memories, avoiding the implementation of frame buffers or any aligning circuitry. The proposed architecture shows state-of-the-art performances in terms of critical path delay, obtaining a critical path delay of 4.7 ns when implemented on a Xilinx Virtex 7 FPGA board. Full article