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The goal of this narrative review was to look at the link between the Mediterranean diet (MD) and the telomere length. Furthermore, this study aims to understand the impact of the MD on obesity-related telomere length.

Relevant literature was reviewed to explore the potential influence of the MD on telomere length and its association with obesity.

The MD is one of the healthiest diets of all known dietary patterns, and it is also linked to the telomere length. Except for fruits and vegetables, the main findings for other MD components are inconsistent. In terms of antioxidant and antiinflammatory properties, using the MD as a weight loss approach is a good method. For predicting changes in obesity characteristics, the initial telomere length is critical. However, there are not many studies in the field that have looked at the MD as a weight loss approach and its link to the telomere length. As a result, more research is needed to understand these connections in various groups.

This study is unique since it examines the MD, telomere length and obesity-related consequences. This study examines the MD, telomere length and obesity to determine if the MD can help lose weight while maintaining telomere length. As there are few studies on MD weight loss and telomere length, the work emphasizes the need for greater research in this area. This study fills a research gap and improves the understanding of nutrition, telomere biology and obesity-related outcomes.

The purpose of this paper aims to design a robust wind turbine emulator (WTE) based on a three-phase induction motor (3PIM).

The 3PIM is driven by a soft voltage source inverter (VSI) controlled by a specific space vector modulation. By adjusting the appropriate vector sequence selection, the desired VSI output voltage allows a real wind turbine speed emulation in the laboratory, taking into account the wind profile, static and dynamic behaviors and parametric variations for theoretical and then experimental analysis. A Mexican hat profile and a sinusoidal profile are therefore used as the wind speed system input to highlight the electrical, mechanical and electromagnetic system response.

The simulation results, based on relative error data, show that the proposed reactive power control method effectively estimates the flux and the rotor time constant, thus ensuring an accurate trajectory tracking of the wind speed for the wind emulation application.

The proposed architecture achieves its results through the use of mathematical theory and WTE topology combine with an online adaptive estimator and Lyapunov stability adaptation control methods. These approaches are particularly relevant for low-cost or low-power alternative current (AC) motor drives in the field of renewable energy emulation. It has the advantage of eliminating the need for expensive and unreliable position transducers, thereby increasing the emulator drive life. A comparative analysis was also carried out to highlight the online adaptive estimator fast response time and accuracy.

Experiencing more frequent, system-wide disruptions, such as pandemics and geopolitical conflicts, supply chains can be largely destabilized by a lack of materials, services or components. Supply chain resilience (SCRES) constitutes the network ability to recover after and survive during such unexpected events. To enhance the understanding of SCRES as a system-wide quality, this study tests a comprehensive SCRES model with data from multiple industries.

The study proposes a theoretical framework conceptualizing SCRES as system quality, extending the classical proactive/reactive taxonomy by multiple system states consisting of the supply system properties, behaviors and responses to disruptions. Underlying hypotheses were tested using an online survey. The sample consists of 219 responses from German industries. Maximum likelihood structural equation modeling (ML-SEM) and moderation analysis were used for analyzing the survey data. The study was particularly designed to elaborate on supply chain theory.

Two pathways of parallel SCRES building were identified: proactive preparedness via anticipation and reactive responsiveness via agility. Both system responses are primarily built simultaneously rather than successively. The present study further provides empirical evidence on the central role of visibility and velocity in achieving comprehensive SCRES, while flexibility only exerts short-term support after a disruption. The study additionally points to potential “spillover effects” such as the vital role of proactive SCRES in achieving reactive responsiveness.

The present study confirms and expands existing theories on SCRES. While stressing the multidimensionality of SCRES, it theorizes the (inter-)temporal evolution of a system and offers practical guidelines for SCRES building in various industrial contexts. It thus supports the transformation toward more resilient and viable supply chains, contributing to the increasing efforts of middle-range theory building to achieve an overarching theory. The study also points to potential future research avenues.

The purpose of this paper is to investigate the efficacy of bacterial exopolysaccharides (Eps) in reactive black 5 (RB5) textile dye wastewater bioremediation.

The Eps were produced by bacteria isolated from cotton gin trash soils collected from different cotton-growing regions in Kenya for comparison purposes. A broth medium reconstituted using molasses was assessed for its capacity to produce the Eps. RB5 textile dye wastewater was optimized for dye removal under different temperatures, times and molasses concentrations. Dye removal was studied by Lovibond-Day Light Comparator, UV–Vis spectrophotometer and FTIR.

It was found that cotton gin trash soils contained Eps-producing bacteria. Three of the Eps studied were found to have the capacity to remove at least 80% of the dye from the wastewater.

This research did not assess the efficacy of the RB5 dye removal from the wastewater by mixtures of the Eps.

Bioremediation of textile dye wastewater with Eps produced by bacteria cultured from cotton gin trash soil is significant because it will offer an effective and cleaner alternative to the chemical coagulants.

Alternative treatment of textile wastewater with the Eps would result in safer water being released into the water bodies as opposed to the chemically treated wastewater that contains remnant chemicals.

Research on the use of Eps produced by bacteria isolated from cotton gin trash soils for removal of RB5 dye from textile wastewater has not been done before.

Recently, powerful instruments for biomedical engineering research studies, including disease modeling, drug designing and nano-drug delivering, have been extremely investigated by researchers. Particularly, investigation in various microfluidics techniques and novel biomedical approaches for microfluidic-based substrate have progressed in recent years, and therefore, various cell culture platforms have been manufactured for these types of approaches. These microinstruments, known as tissue chip platforms, mimic in vivo living tissue and exhibit more physiologically similar vitro models of human tissues. Using lab-on-a-chip technologies in vitro cell culturing quickly caused in optimized systems of tissues compared to static culture. These chipsets prepare cell culture media to mimic physiological reactions and behaviors.

The authors used the application of lab chip instruments as a versatile tool for point of health-care (PHC) applications, and the authors applied a current progress in various platforms toward biochip DNA sensors as an alternative to the general bio electrochemical sensors. Basically, optical sensing is related to the intercalation between glass surfaces containing biomolecules with fluorescence and, subsequently, its reflected light that arises from the characteristics of the chemical agents. Recently, various techniques using optical fiber have progressed significantly, and researchers apply highlighted remarks and future perspectives of these kinds of platforms for PHC applications.

The authors assembled several microfluidic chips through cell culture and immune-fluorescent, as well as using microscopy measurement and image analysis for RNA sequencing. By this work, several chip assemblies were fabricated, and the application of the fluidic routing mechanism enables us to provide chip-to-chip communication with a variety of tissue-on-a-chip. By lab-on-a-chip techniques, the authors exhibited that coating the cell membrane via poly-dopamine and collagen was the best cell membrane coating due to the monolayer growth and differentiation of the cell types during the differentiation period. The authors found the artificial membrane, through coating with Collagen-A, has improved the growth of mouse podocytes cells-5 compared with the fibronectin-coated membrane.

The authors could distinguish the differences across the patient cohort when they used a collagen-coated microfluidic chip. For instance, von Willebrand factor, a blood glycoprotein that promotes hemostasis, can be identified and measured through these type-coated microfluidic chips.

The purpose of this paper is to solve the problem that mobile robots are still based on reactive collision avoidance in unknown dynamic environments leading to a lack of interaction with obstacles and limiting the comprehensive performance of mobile robots. A dynamic window approach with multiple interaction strategies (DWA-MIS) is proposed to solve this problem.

The algorithm firstly classifies the moving obstacle movement intention, based on which a rule function is designed to incorporate positive incentives to motivate the robot to make correct avoidance actions. Then, the evaluation mechanism is improved by considering the time cost and future information of the environment to increase the motion states. Finally, the optimal objective function is designed based on genetic algorithm to adapt to different environments with time-varying multiparameter optimization.

Faced with obstacles in different states, the mobile robot can choose a suitable interaction strategy, which solves the limitations of the original DWA evaluation function and avoids the defects of reactive collision avoidance. Simulation results show that the algorithm can efficiently adapt to unknown dynamic environments, has less path length and iterations and has a high comprehensive performance.

A DWA-MIS is proposed, which increases the interaction capability between mobile robots and obstacles by improving the evaluation function mechanism and broadens the navigation strategy of DWA at a lower computational cost. After real machine verification, the algorithm has a high comprehensive performance based on real environment and provides a new idea for local path planning methods.

This paper aims to investigate the bonding of the photonic integrated circuit (PIC) chip with the heat sink using the AlNi self-propagating soldering method.

Compared to industrial optical modules, optical modules for aerospace applications require better reliability and stability, which is hard to achieve via the dispensing adhesive process that is used for traditional industrial optical modules. In this paper, 25 µm SAC305 solder foils and the AlNi nanofoil heat source were used to bond the back of the PIC chip with the heat sink. The temperature field and temperature history were analyzed by the finite element analysis (FEA) method. The junction-to-case thermal resistance is 0.0353°C/W and reduced by 85% compared with the UV hybrid epoxy joint.

The self-propagating reaction ends within 2.82 ms. The maximum temperature in the PIC operating area during the process is 368.5°C. The maximum heating and cooling rates of the solder were 1.39 × 107°C/s and −5.15 × 106°C/s, respectively. The microstructure of SAC305 under self-propagating reaction heating is more refined than the microstructure of SAC305 under reflow. The porosity of the heat sink-SAC305-PIC chip self-propagating joint is only 4.7%. Several metastable phases appear as AuSn3.4 and AgSn3.

A new bonding technology was used to form the bonding between the PIC chip with the heat sink for the aerospace optical module. The reliability and thermal resistance of the joint are better than that of the UV hybrid epoxy joint.

Accurate prediction of the structural condition of urban critical infrastructure is crucial for predictive maintenance. However, the existing prediction methods lack precision due to limitations in utilizing heterogeneous sensing data and domain knowledge as well as insufficient generalizability resulting from limited data samples. This paper integrates implicit and qualitative expert knowledge into quantifiable values in tunnel condition assessment and proposes a tunnel structure prediction algorithm that augments a state-of-the-art attention-based long short-term memory (LSTM) model with expert rating knowledge to achieve robust prediction results to reasonably allocate maintenance resources.

Through formalizing domain experts' knowledge into quantitative tunnel condition index (TCI) with analytic hierarchy process (AHP), a fusion approach using sequence smoothing and sliding time window techniques is applied to the TCI and time-series sensing data. By incorporating both sensing data and expert ratings, an attention-based LSTM model is developed to improve prediction accuracy and reduce the uncertainty of structural influencing factors.

The empirical experiment in Dalian Road Tunnel in Shanghai, China showcases the effectiveness of the proposed method, which can comprehensively evaluate the tunnel structure condition and significantly improve prediction performance.

This study proposes a novel structure condition prediction algorithm that augments a state-of-the-art attention-based LSTM model with expert rating knowledge for robust prediction of structure condition of complex projects.

The aggressive competition in the real estate market forces real estate developers to tackle the challenge of selecting the best project construction phasing alternative. The real estate industry is characterized by high costs, high profit and high risks. The schedules of real estate projects are also characterized by having large number of repetitive activities that are executed over a long duration. The repetitiveness, long duration of execution, the high amounts of money involved and the high risk made it desirable to leverage the impact of changes in phasing plans on net present value of amounts incurred and received over the long execution and selling duration. This also changes the project progress, and delivery time as well as their respective impact on customer degree of satisfaction. This research addresses the problem of selecting the best phasing alternative for real estate development projects while maximizing customer satisfaction and project profit.

The research proposes a model that generates all construction phasing alternatives and performs decision-making to rank all possible phasing alternatives. The proposed model consists of five modules: (1) Phasing Sequencing module, (2) Customer Satisfaction module, (3) Cash-In calculation module, (4) Cost Estimation module and (5) Decision-making module. A case study was presented to demonstrate the practicality of the model.

The proposed model satisfies the real estate market's need for proper construction phasing plans evaluation and selection against the project's main success criteria, customer satisfaction and project profit. The proposed model generates all construction phasing alternatives and performs multi-criteria decision making to rank all possible phasing alternatives. It quantifies the score of the two previously mentioned criteria and ranks all solutions according to their overall score.

The research proposes a model that assist real estate market's need for proper construction phasing plans evaluation and selection against the project's main success criteria, customer satisfaction and project profit. The proposed model can be used to conclude general guidelines and common successful practices to be used by real estate developers when deciding the construction phasing plan. In this study the model is based on business models where all the project units are sold, rental cases are not considered. Also, the budget limitations that might exist when phasing is not considered in the model computations.

The model can be used as a complete platform that can hold all real estate project data, process revenues and cost information for estimating profit, plotting cash flow profiles, quantifying the degree of customer satisfaction attributable to each phasing alternative and providing recommendation showing the best one. The model can be used to conclude general guidelines and common successful practices to be used by real estate developers when tackling the challenge of selecting construction phasing plans.

This study aims to examine the effect of Industry 4.0 technology on resilience in established cross-border supply chain(s) (SC).

A literature review provides insight into the resilience capabilities of cross-border SC. The research uses a case study of operational international SC: the producers, importers, logistics companies and UK Government (UKG) departments. Semi-structured interviews determine the resilience capabilities and approaches of participants within cross-border SC and how implementing an Industry 4.0 Internet of Things (IoT) and capitals Distributed Ledger (blockchain) based technology platform changes SC resilience capabilities and approaches.

A blockchain-based platform introduces common assured data, reducing data duplication. When combined with IoT technology, the platform improves end-to-end SC visibility and information sharing. Industry 4.0 technology builds collaboration, trust, improved agility, adaptability and integration. It enables common resilience capabilities and approaches that reduce the de-coupling between government agencies and participants of cross-border SC.

The case study presents challenges specific to UKG’s customs border operations; research needs to be repeated in different contexts to confirm findings are generalisable.

Operational SC and UKG customs and excise departments must align their resilience strategies to gain full advantage of Industry 4.0 technologies.

Case study research shows how Industry 4.0 technology reduces the de-coupling between the SC and UKG, enhancing common resilience capabilities within established cross-border operations. Improved information sharing and SC visibility provided by IoT and blockchain technologies support the development of resilience in established cross-border SC and enhance interactions with UKG at the customs border.