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The purpose of this study was to determine the effect of exercise intensity on the proportion and rate of carbohydrate oxidation and glucoregulatory hormone responses during recovery from exercise. Six physically active participants completed 1 hr of low-intensity (LI; 50% lactate threshold) or moderate-intensity (MI; 100% lactate threshold) exercise on separate days following a randomized counterbalanced design. During exercise and for 6 hr of recovery, samples of expired air were collected to determine oxygen consumption, respiratory exchange ratio, energy expenditure, and substrate oxidation rates. Blood samples were also collected to measure glucoregulatory hormones (catecholamines, GH) and metabolites (glucose, free fatty acids, lactate, pH, and bicarbonate). During exercise, respiratory exchange ratio, energy expenditure, and the proportion and rate of carbohydrate (CHO) oxidation were higher during MI compared with LI. However, during recovery from MI, respiratory exchange ratio and the proportion and rate of CHO oxidation were lower than preexercise levels and corresponding LI. During exercise and early recovery, catecholamines and growth hormone were higher in MI than LI, and there was a trend for higher levels of free fatty acids in the early recovery from MI compared with LI. In summary, CHO oxidation during exercise increases with exercise intensity but there is a preference for CHO sparing (and fat oxidation) during recovery from MI exercise compared with LI exercise. This exercise intensity-dependent shift in substrate oxidation during recovery is explained, in part, by the pattern of change of key glucoregulatory hormones including catecholamines and growth hormone and plasma fatty acid concentrations. [ABSTRACT FROM AUTHOR]

As more distributed energy resources become part of the demand-side infrastructure, quantifying their energy flexibility on a community scale is crucial. CityLearn v1 provided an environment for benchmarking control algorithms. However, there is no standardized environment utilizing realistic building-stock datasets for distributed energy resource control benchmarking without co-simulation or third-party frameworks. CityLearn v2 extends CityLearn v1 by providing a stand-alone simulation environment that leverages the End-Use Load Profiles for the U.S. Building Stock dataset to create grid-interactive communities for resilient, multi-agent, and objective control of distributed energy resources with dynamic occupant feedback. While the v1 environment used pre-simulated building thermal loads, the v2 environment uses data-driven thermal dynamics and eliminates the need for co-simulation with building energy performance software. This work details the v2 environment and provides application examples that use reinforcement learning control to manage battery energy storage system, vehicle-to-grid control, and thermal comfort during heat pump power modulation. [ABSTRACT FROM AUTHOR]

Purpose: Given the sudden increase in plant investments across the manufacturing sector due to recent disruptions in the global supply chain caused by the COVID pandemic, the Ukraine/Russian war, ocean piracy incidents, and others, there is a need to strategically align the investments decisions with the overall business strategy. This study aims to establish whether strategic alignment enhances the effect of plant investments on operational performance. Design/methodology/approach: Using the fifth version of the Global Manufacturing Research Group (GMRG V) dataset, we employ a structural equation model (SEM) to establish the moderating role of strategic alignment in plant investments-operational performance relationships. Findings: The results suggest that strategic alignment enhances the positive effect of plant investments on operational performance, especially in cost, delivery, flexibility, and innovation. However, we found partial support for the moderating role of strategic alignment on quality performance. Research limitations/implications: Although the study was based on the GMRG global dataset and numerous papers have been published using the same dataset, the use of a convenience sample on a select group of companies may limit the generalizability of the results. With the increase in new plant investments in computer chip manufacturing, electronics, and electrical in recent years, the findings could help corporate executives maximize the benefits of their investment decisions. Companies should ensure that their plant investment decisions are strategically aligned with their overall business strategy to achieve optimal outcomes. Practical implications: With the increase in new plant investments in computer chip manufacturing, electronics, and electrical in recent years, the findings could help corporate executives maximize the benefits of their investment decisions. Companies should ensure that their plant investment decisions are strategically aligned with their overall business strategy to achieve optimal outcomes. Originality/value: The study comprehensively demonstrates that the extent of improvement in operational performance depends on how closely plant investment decisions align with the overall company strategy. Manufacturers should align major investment decisions with competitive priorities driven by market requirements to enhance operational performance. [ABSTRACT FROM AUTHOR]

Background: In the pursuit of sustainable energy sources, residual biomass has emerged as a promising renewable resource. However, efficiently managing residual biomass poses significant challenges, particularly in optimizing supply chain operations. Advanced modeling approaches are necessary to address these complexities. This study aims to develop a comprehensive methodological framework for creating simulation models tailored to agroforestry residual biomass supply chains. Methods: The study employs a hybrid simulation approach, integrating geographic information system mapping with a case study analysis. The simulation was conducted over a 365-day period, using the anyLogistix software (version 2.15.3.202209061204) to model various supply chain dynamics. The framework also accounts for financial, operational, customer satisfaction, and environmental metrics. Results: The simulation results showed a total expenditure of EUR 5,219,411.3, with transportation being the primary cost driver, involving 5678 trips and a peak capacity of 67.16 m3. CO2 emissions were measured at 487.7 kg/m3. The model performed as expected, highlighting the need for sustainable logistics strategies to reduce costs, lower losses, and improve productivity. Conclusions: This study presents one of the first detailed methodological frameworks for simulating agroforestry residual biomass supply chains. It provides valuable managerial insights into the financial, operational, and environmental aspects of supply chain management. The findings may stakeholders make informed decisions to enhance the sustainability of biomass utilization in energy production. [ABSTRACT FROM AUTHOR]

As environmental sustainability gains importance, enhancing supply chains to minimize environmental hazards is essential, particularly in industries using residual biomass. This study tackles this by investigating the integration of sustainability criteria into supply chain optimization for a biomass energy company in Portugal, using a combination of simulation modeling through anyLogistix software (version: 2.15.3.202209061204) and multi-criteria decision-making. Four supply chain scenarios were designed and simulated, differing in their number of distribution centers, the adoption of green logistics, and split-by-ratio distribution strategies over a 305-day period. Through the weighted sum model, Scenario C emerged as the optimal configuration, achieving a balance between operational efficiency and sustainability by reducing CO2 emissions by up to 90% and lowering transportation costs without compromising revenue. Sensitivity analysis further highlighted the trade-offs between cost efficiency, lead times, and environmental impact, showing that the strategic placement of distribution centers and the use of eco-friendly vehicles significantly improve the sustainability of the biomass supply chain. These findings provide practical insights for decision-makers, demonstrating how digital modeling tools can enhance supply chain management by optimizing environmental and operational goals simultaneously. This research contributes to the fields of sustainable logistics and supply chain management by validating the effectiveness of green logistics strategies and multi-criteria decision-making approaches in reducing environmental impact while maintaining economic viability. [ABSTRACT FROM AUTHOR]

The mid-face has been rendered as the cornerstone of facial aesthetic improvement, since treating the mid-face has also beneficial effects on neighboring esthetic units and therefore should be one of the first areas to be assessed. Retaining ligaments (RL) bind soft tissue layers of the face to the underlying facial skeleton. It remains controversial whether RL suffers laxity with aging or if changes in 42 bone and other structures where ligaments are inserted lead to altered mechanical function of the latter. Enhancement of the supportive effect of the ligaments could help restore the soft tissues to their original anatomical positions and achieve a lifting effect. While injectable hyaluronic acid implants have been used to improve ligament support, calcium hydroxylapatite has one of the highest viscoelasticities when compared with other dermal fillers and can induce collagen synthesis, which could provide long-term laxity correction. In this preliminary report of a case series, our goal was to describe the use of calcium hydroxylapatite in different dilutions and combinations for different aging profiles to treat the midface as an alternative for hyaluronic acid injections and to describe the ultrasonographic behavior in the long run. [ABSTRACT FROM AUTHOR]

Objective: Individual unsupervised home-based exercise programs can enhance muscle strength, physical function, gait, and balance in older adults. However, the effectiveness of such programs may be limited by the lack of supervision. This study aims to verify the effectiveness of individual unsupervised home-based programs, compare the effects of individual unsupervised home-based to supervised programs, and verify the influence of supervision over individual unsupervised home-based programs on the physical function of older adults. Methods: A systematic literature search was performed in four electronic databases, and the trials involved randomized controlled comparing the home-based programs to supervised, control groups, or home-based + supervised evaluating the muscle strength, physical function, gait, and balance in older adults. Results: Eleven studies met the inclusion criteria. The meta-analysis revealed no differences between home-based program versus supervised program in gait, mobility, and balance, revealing a trend of significance to supervised program on strength (standardized mean difference [SMD] = 0.27, p =.05). The analysis revealed effects in mobility (SMD = 0.40, p =.003), balance (SMD = 0.58, p =.0002), and muscle strength (SMD = 0.36, p =.02) favoring home-based program versus control group. Significant effects between home-based program versus home-based + supervised program were observed in balance (SMD = 0.74, p =.002) and muscle strength (SMD = 0.58, p =.01) in favor of home-based + supervised program. Conclusion: Home-based programs effectively improve older adults' physical function compared with control groups. However, supervised programs were more effective for muscle strength. [ABSTRACT FROM AUTHOR]