Mixed Programming Research Articles

Optimal Operation of CCHP Smart Distribution Grid with Integration of Renewable Energy

Recently, electric distribution grids supply not only electric loads but also heating and cooling loads simultaneously to increase the efficiency of the system and reduce the emission of greenhouse gases. An energy management system (EMS) to reduce the combined total expense including environmental damage cost of the combined cooling, heating, and power (CCHP) smart distribution grids in a cooperative framework is proposed in this paper. The entire problem is modelled as a unit commitment interval mixed integer quadratic program (UCIMIQP). The UC is developed to respond to the operation of the electric, heating, and cooling systems and takes into consideration the exchange of energy between these systems. In addition, the demand response (DR) is incorporated with the optimization problem as a decision variable to shave the peak load and reduce the total system cost. The environmental damage is converted to expense, and the entire combined problem is converted to a unified function that is possible to solve in one step, where this is suitable for online operation. Furthermore, a set of realistic constraints is considered to make the approach close to a real scenario. To verify the effectiveness and robustness of the proposed model, the analysis is applied to the distribution grids, which include electrical, heating, and cooling systems, where these systems operated cooperatively. The interaction between these systems makes the operation more flexible and economical. The results show that the total cost is reduced through an exchange in energy between the systems. Additionally, the consideration of the demand response reduces the maximum load and decreases the total cost.

A mixed methods investigation of Indigenous university students' experiences with and strategies to challenge racism.

In this mixed methods program of research, we investigated Indigenous participants' experiences with racism at a Canadian postsecondary institution. In Study 1 (N = 8), we interviewed Indigenous students or recent graduates about their experiences with racism and thematically analyzed their responses. We asked questions about what participants thought racism was, how frequently they experienced racism, how experiencing racism made them feel, which racist incidents were the most important to challenge, how they dealt with racism, and their positive experiences on campus as an Indigenous person. In Study 2 (N = 485), we surveyed Indigenous students about their experiences with racism. Participants responded to items about the frequency of potentially racist incidents, how those incidents made them feel, and if they considered those incidents as racist. They also responded to items about positive race-based experiences and their feelings about their on-campus experience. In Study 1, participants experienced many different types of racism: internalized (including racial microaggressions, modern racism, and old-fashioned racism), interpersonal, institutional, and structural. They also shared the negative impacts of experiencing racism and the ways they challenged and coped with racism. In Study 2, participants indicated that they experienced racism on campus regularly and that these experiences tended to make them feel bad. Participants also experienced positive race-based experiences and felt good in these cases. Anti-Indigenous racism happens with alarming regularity at the institution and negatively impacts Indigenous participants, though participants actively push back against racism. We discuss the implications and future research directions. (PsycInfo Database Record (c) 2025 APA, all rights reserved).

Effects of physical exercise on anxiety depression and emotion regulation in children with attention deficit hyperactivity disorder: a systematic review and meta-analysis.

This systematic review and meta-analysis aimed to comprehensively evaluate the impact of physical exercise interventions on anxiety, depression, and emotional regulation in children diagnosed with attention deficit hyperactivity disorder (ADHD). A comprehensive search was conducted across multiple databases, including Embase, Web of Science (WOS), PubMed, The Cochrane Library, Wanfang Data, VIP Information, and China National Knowledge Infrastructure (CNKI), from their inception up to July 2024. The search aimed to identify randomized controlled trials (RCTs) investigating the impact of physical exercise on anxiety, depression, and emotional regulation in children diagnosed with ADHD. The Physiotherapy Evidence Database (PEDro) scale was employed to assess the quality of the literature, while the revised Cochrane risk-of-bias tool (ROB-2) was used to evaluate the overall risk of bias. The Grading of Recommendations, Assessment, Development and Evaluation (GRADE) profiler method was utilized to further assess the quality of evidence. Meta-analysis, sensitivity analysis, and publication bias testing were performed using Stata 18.0 software. Effect sizes were calculated using the standardized mean difference (SMD) and 95% confidence intervals (CI). The analysis included 18 RCTs, encompassing 830 participants. Physical exercise exhibited a significant positive effect on anxiety (SMD = -0.58, p < 0.05), depression (SMD = -0.57, p < 0.05), and emotional regulation (SMD = 1.03, p < 0.05) in children diagnosed with ADHD. Subgroup analysis revealed that exercise programs with monotypic and mixed modalities, short duration, high frequencies, medium duration, and moderate intensities were the most efficacious in ameliorating anxiety symptoms. The mixed exercise program, when conducted for short duration, with low frequencies, medium duration, and moderate intensity was the most effective in alleviating depression symptoms. Exercise programs featuring mixed modalities, longer duration, moderate to high frequencies, shorter duration, and low intensity yielded the most significant improvements in emotional regulation. Research demonstrates that physical exercise mitigates anxiety and depression and improves emotional regulation in children with ADHD. A dose-response relationship is evident, correlating with the type, duration, intensity, frequency, and overall exercise duration. https://www.crd.york.ac.uk/prospero/, PROSPERO identifier (CRD42024571577).

Otolith stable isotopes highlight the importance of local nursery areas as the origin of recruits to yellowfin tuna (Thunnus albacares) fisheries in the western Indian Ocean

Yellowfin tuna (Thunnus albacares) supports the second largest tuna fishery worldwide, and in the Indian Ocean, it is overfished and subject to overfishing. This situation presents a significant challenge to fisheries management, requiring effective measures to rebuild and then maintain the stock at sustainable levels. A single stock of yellowfin is currently assumed by the Indian Ocean Tuna Commission (IOTC) for stock assessments in the Indian Ocean. However, the relative contribution of different spawning components to the total catches, and the degree of mixing rates of yellowfin tuna in the Indian Ocean by individuals from different production zones, are still unknown. This study uses otolith core oxygen and carbon stable isotope composition (δ18O and δ13C) of young-of-the-year yellowfin tuna from nursery areas located in the western (FAO Area 51) and eastern (FAO area 57) Indian Ocean, either side of 80ºE, to establish a reference baseline of isotopic signatures. Then, a mixed population program (HISEA) and Random Forest (RF) assignment approaches were used to predict the most likely origin (west or east) of sub-adult and adult yellowfin tuna captured from four fishery areas of the western Indian Ocean (offshore Pakistan, Seychelles, Reunion, and South Africa) by comparing their otolith core values to that of the baseline. Both approaches show that the western Indian Ocean fisheries are mainly composed of west origin fish (>95%). We also found some individuals with an otolith isotopic signature that was not characteristic of either of the samples available in the baseline. We simulated an alternative baseline group formed by individuals with mean and standard deviation δ13C and δ18O values above the maximum ranges of the original baseline. We then used RF to infer again the most likely origin of fish in the mixed sample considering 3 possible sources (west, east, alternative). About one third of the samples were assigned to the alternative group, possibly indicating that they differ in geographical or temporal terms with the origins represented in the original baseline. Findings of otolith stable isotope composition of yellowfin tuna in the western Indian Ocean can provide a more comprehensive understanding of the species’ spatial structure and connectivity beyond the current assumption of an ocean basin single stock.

Research and Discussion on the Construction of Curriculum Resource System Based on the Background of Educational Informatization

In the modern era, the cultivation of foreign talents extends beyond the traditional enhancement of humanistic knowledge, with literature playing a pivotal role. Addressing the challenges posed by the “golden curriculum,” this study uses the “Selected British and American Stories” program as an example to explore a blended learning and sorting approach. Aligned with the Ministry of Education’s emphasis on “golden subjects,” the research formulates an implementation strategy for curriculum development. In the context of the Ministry’s promotion of the mixed funding program in 2019, the study highlights the necessity of guiding students to utilize the Internet for data-driven blended learning. By emphasizing active engagement, intrinsic motivation, and flexible learning approaches, the proposed strategy aims to enhance teaching quality and align with contemporary educational reform priorities. Furthermore, the paper underscores the significance of equitable teaching evaluation as a feedback mechanism, actively contributing to the overall improvement of teaching quality.

Determinants of adherence towards tuberculosis guidelines among Indonesian private practitioners: a qualitative study

IntroductionIn high tuberculosis (TB) burden countries, the private sector manages a large proportion of initial visits by presumptive patients with TB. In Indonesia, the second largest contributor of TB cases...

Real-time executable platoon formation approach using hierarchical cooperative motion planning framework

While connected and automated vehicle (CAV) platooning holds promise for enhancing traffic efficiency and reducing energy consumption, we still lack efficient algorithms for guiding the local movements of CAVs to form a platoon on a road due to significant computational and control challenges. This study addresses this gap by designing a real-time executable Hierarchical and Recursive Platoon Formation (HR-PF) framework tailored to mixed flow traffic conditions that encompass both Human-Driven Vehicles (HDV) and CAVs. The HR-PF framework comprises three hierarchical mathematical models (modules) designed to optimize platoon formation while considering both macroscopic traffic conditions and microscopic traffic safety. Module-I formulates a mixed integer quadratic program to determine the timing, location, and state of platoon formation. It is further extended to a mixed integer nonlinear program so that we can also select the optimal size of the target platoon. Module-II designs a Hybrid State-Lattice Motion planner to generate optimal trajectory references for CAVs to approach the target platoon state, ensuring microscopic traffic safety. Module-III develops longitudinal and lateral controllers to enable CAVs to track trajectory references accurately. These models function recursively at varying frequencies to balance mathematical rigor with practical application. Numerical experiments demonstrate that HR-PF facilitates efficient platoon formation in real-time across diverse traffic scenarios and road geometries while sustaining traffic efficiency. Furthermore, the performance of platoon formation is affected by surrounding traffic density and CAV penetrations, with prompt formation observed under LOS C and D traffic environments and slightly more traffic impacts under LOS E and F. These findings provide robust support for exploring advanced platoon formation and platooning strategies for CAVs under complicated traffic environments.

A hierarchical intersection system control framework in mixed traffic conditions

Signalized intersections play a crucial role in urban road system and are a significant source of vehicle delays. Conventional intersection control methods struggle to cope with increasingly challenging traffic conditions. Fortunately, the development of artificial intelligence(AI), information communication technology(ICT) and connected and automated vehicle(CAV) technologies has brought new opportunities to enhance traffic performance at intersections. Based on these technologies, in the mixed traffic environment of CAVs and connected human-driven vehicles (CHVs), this paper proposes a hierarchical intersection system control framework, which adopts intersection level distributed control and corridor level centralized control. At the intersection level, considering the impact of CAV-dedicated lanes and using the CAV platoon and “1 + n” platoon consisting of one leading CAV and n following CHVs as control units, the mixed integer quadratic programming problem and optimal control problem are formulated to collaboratively optimize signal timing, lane settings and vehicle trajectories at isolated signalized intersections. At the corridor level, based on the optimization results of the intersection level and the critical path information, the critical path performance function and multi-stage optimal trajectory control formula are constructed to optimize the signal offsets and vehicle trajectories, which are passed to the intersection level, and ultimately minimize vehicle delays in the corridor. Simulation experiments and sensitivity analysis demonstrate the effectiveness and stability of the proposed framework in reducing vehicle delay and improving fuel consumption.

An Optimization Strategy for Unit Commitment in High Wind Power Penetration Power Systems Considering Demand Response and Frequency Stability Constraints

To address the issue of accommodating large-scale wind power integration into the grid, a unit commitment model for power systems based on an improved binary particle swarm optimization algorithm is proposed, considering frequency constraints and demand response (DR). First, incentive-based DR and price-based DR are introduced to enhance the flexibility of the demand side. To ensure the system can provide frequency support, the unit commitment model incorporates constraints such as the rate of change of frequency, frequency nadir, steady-state frequency deviation, and fast frequency response. Next, for the unit commitment planning problem, the binary particle swarm optimization algorithm is employed to solve the mixed nonlinear programming model of unit commitment, thus obtaining the minimum operating cost. The results show that after considering DR, the load becomes smoother compared to the scenario without DR participation, the overall level of load power is lower, and the frequency meets the safety constraint requirements. The results indicate that a comparative analysis of unit commitment in power systems under different scenarios verifies that DR can promote rational allocation of electricity load by users, thereby improving the operational flexibility and economic efficiency of the power system. In addition, the frequency variation considering frequency safety constraints has also been significantly improved. The improved binary particle swarm optimization algorithm has promising application prospects in solving the accommodation problem brought by large-scale wind power integration.

Evaluating Treatment Characteristics and Outcomes for Juvenile Sexual Offenders: A Review

Improving treatment effectiveness for adolescent sexual offenders is believed to be able to reduce the number of recidivism. This review aims to evaluate treatment characteristics and outcomes for the juvenile sexual offender. Existing treatments focus on sexual behavior management, primarily with cognitive behavioral theory and social learning theory. This study used EBSCO databases related to psychology science, such as Academic Search Complete, APA PsycArticles, MEDLINE, and APA PsycINFO. The search was for peer-reviewed empirical studies published between January 2010 and February 2020 with the inclusion criteria that focus on the treatment outcomes evaluations. Eleven studies categorized as mixed therapy programs, family-based treatments, and other specific treatments were reviewed and revealed limitations in methodology, which contributes to the obstruction of treatment evaluation. The key finding of this study suggests the developmental aspect of juvenile sexual offenders when designing interventions and effectivity measurements. Previous treatments for juvenile sexual offenders have developed with several approaches, such as cognitive behavioral perspectives and social learning theory. Keywords: juvenile sexual offender ( JSO), treatment, treatment evaluation

Speech in noise performance in adults with cochlear implants using a combined channel deactivation strategy with a variable number of dynamic focused channels.

Cochlear implant listeners show difficulties in understanding speech in noise. Channel interactions from activating overlapping neural populations reduce the signal accuracy necessary to interpret complex signals. Optimizing programming strategies based on focused detection thresholds to reduce channel interactions has led to improved performance. In the current study, two previously suggested methods, channel deactivation and focused dynamic tripolar stimulation, were combined to create three cochlear implant programs. Utilizing an automatic channel selection algorithm from focused detection threshold profiles, three programs were created with the same deactivated channels but varying proportions of channels employing focused stimulation, monopolar, dynamic focused and a mixed program. Thirteen ears in eleven adult cochlear implant listeners with Advanced Bionics HiRes90k devices were tested. Vowel identification and sentence perception in quiet and noise served as outcome measures, and the influences of listening experience, age, clinical consonant-nucleus-consonant performance, and perceptual thresholds on speech performance were assessed. Across subjects, different degrees of focusing showed individual performance improvements for vowels and sentences over the monopolar program. However, only slight trends and no significant group improvements were observed. Focused listening benefits were shown for individuals with less cochlear implant experience, and clinically poor performers seem to benefit more from focusing than good performers. The current findings suggest that deactivating and focusing subsets of channels improves speech performance for some individuals, especially poor performers, a possible effect of reduced channel interactions. The findings also show that individual performance is largely variable, possibly due to listening experience, age or the underlying detection threshold.

Development and Validation of Virtual Reality Cognitive Training for Older Adults with Mild Cognitive Impairment: Protocol for a Mixed-Methods Program Evaluation Study.

As research on cognitive training methods for older adults with mild cognitive impairment (MCI) progresses, fully immersive virtual reality cognitive training (fi-VRCT) has shown promise in enhancing cognitive function. However, its effectiveness in improving instrumental activities of daily living (IADL) and fostering independence is still unclear. This study aims to address these uncertainties by developing and validating a fi-VRCT program focused on IADL, with the goal of enhancing both cognitive function and IADL performance in older adults with MCI. This mixed methods program evaluation study consists of three phases: feasibility, intervention, and extension. In the feasibility phase, we will implement fi-VRCT in real-world community settings and invite 20 older adults with MCI to participate in a single training session. Participants will provide feedback through questionnaires and individual interviews. The intervention phase will involve a double-blind, cluster-randomized controlled trial with 52 older adults with MCI, who will be randomly assigned to either the fi-VRCT or control groups. Both groups will complete 16 sessions over eight weeks, with cognitive and functional performance assessed at various intervals. During the extension phase, feedback will be gathered from 26 participants who underwent fi-VRCT through focus group interviews and ongoing questionnaires. Quantitative and qualitative findings will be synthesized to refine the fi-VRCT program and elucidate training outcomes. Ultimately, fi-VRCT has the potential to enhance cognitive and functional abilities in older adults with MCI in community settings. Ethical approval has been obtained from the Research Ethics Committee at National Taiwan Normal University (202312EM009). The research findings will be disseminated through reputable, peer-reviewed journals and professional international conferences to engage and inform academic and clinical audiences. NCT06392412.

Exploring Carbon Equilibrium in Integrated Electricity–Hydrogen System

Global carbon emissions from electricity and hydrogen production have grown rapidly in recent years. Some existing literature has proposed the method of reducing carbon emissions by power-to-hydrogen (P2H) technology. However, due to the fossil-based energy structure of electricity system, excessive electricity to hydrogen may lead to an increase in carbon emissions. To reduce carbon emissions effectively, a low carbon-driven optimal capacity configuration method for P2Hs is proposed in this paper to explore carbon equilibrium in integrated electricity-hydrogen system. A joint economic dispatch model for integrated electricity-hydrogen system is formulated. The electricity system model is a security-constrained economic dispatch model with P2H constraints. The hydrogen system model is a hydrogen supply chain model with pipeline pack constraints and Weymouth equation, whose sources are fossil fuel reforming and electrolytic hydrogen. We propose a second-order cone programming (SOCP)-based solution to transform the hydrogen system model into a mixed integer second order cone programming (MISCOP), which can be readily solved by commercial solvers. To preserve the internal information of each system, a decentralized algorithm based on optimality condition decomposition (OCD) is developed. Case study based on modified IEEE 30-bus and Belgium 20-node integrated energy system demonstrates the effectiveness of the proposed strategy.

The Impact of Components in Marketing - Mix Strategy on Customer Satisfaction and Loyalty: Case Study at Codegym Vietnam Joint Stock Company, Hue Branch

This study aims to analyze the impact of 7 components on the marketing - mix strategy on the satisfaction and loyalty of programming course students at the branch of CodeGym Vietnam Joint Stock Company in Hue. The study combined exploratory factor analysis (EFA), and confirmatory factor analysis (CFA) to measure the impacts of each component into the success of marketing - mix strategy then applied linear structural modeling (SEM) to test the related hypothesis of driving parameters to the customers’ satisfaction and loyalty. The finding indicated that there are 3 major factors having positively impact on customer satisfaction and loyalty, including: product, distribution and process. On the contrary, price, promotion, people and facilities factors have a negative impact on student satisfaction. The study also suggests several important implications to enhancing the efficiency of marketing mix strategy - with a need to focusing on developing marketing mix programs for centers to enhance customer satisfaction and loyalty.

Kinect-Based Mixed Reality Exercise Program Improves Physical Function and Quality of Life in Breast Cancer Survivors: A Randomized Clinical Trial.

Exercise is an effective non-pharmacological approach for alleviating treatment-related adverse effects and enhancing physical fitness in breast cancer survivors. A Kinect-based mixed reality device (KMR), with real-time feedback and user data collection, is an innovative exercise intervention for breast cancer survivors. This study aimed to investigate the effect of KMR exercise program on quality of life (QOL) and physical function in breast cancer survivors. Seventy-seven participants were randomly assigned to either the KMR exercise group or home stretching group with an 8-week intervention. Physical function (shoulder range of motion [ROM], body composition, aerobic capacity, and hand grip strength) was evaluated before and after the intervention period. Participants completed questionnaires such as the Disabilities of the Arm, Shoulder, and Hand (DASH), Functional Assessment of Cancer Therapy-Breast, and International Physical Activity Questionnaire (IPAQ) to assess upper extremity disabilities, QOL, and physical activity levels. Significant group-by-time interaction was found for flexion of the operated arm (154.3±12.5 to 165.8±11.2), and the non-operated arm (158.2±13.8 to 166.5±12.2), abduction of the non-operated arm (154.8±31.6 to 161.1±28.1), and adduction of the operated arm (46.5±9.1 to 52.6±7.2). Significant improvements were also observed in DASH (46.8±9.1 to 40.8±9.3) and IPAQ (1136.3±612.8 to 1287±664.1). The KMR exercise program effectively improved the physical function, alleviated edema, reduced upper extremity disability, and enhanced the QOL in breast cancer survivors. Coupled with significant group-by-time interactions for various outcomes, the results emphasize the potential benefits of incorporating the KMR exercise program to improve the QOL in breast cancer survivors.

Joint optimal PMU and DULR placement in distribution network considering fault reconstruction and state estimation accuracy

Due to the rapid development of the distribution network, there is an urgent need for high-precision state estimation and safe and stable operation, this paper proposes a joint optimal placement method for Phasor Measurement Unit (PMU) and Dual Use Line Relay (DULR) in distribution networks considering fault reconstruction and state estimation accuracy. The proposed method aims to minimize the cost of PMU and DULR configuration. Based on the known pseudo-measurements and Supervisory Control and Data Acquisition (SCADA) measurements, we use the E-optimal standard design of the state estimation error covariance matrix to form the state estimation accuracy index and take the relay protection function of Feeder Terminal Unit (FTU) device and DULR device into consideration of the fault reconstruction. By solving the mixed integer semidefinite programming (MISDP) model, the optimal placement result is obtained, so that the network under normal condition and the network after multiple fault reconstruction can meet the constraints of state estimation accuracy and load loss rate respectively. The proposed method is tested on IEEE 33-node, 123-node systems as an example. The experimental results show that the proposed method is effective and practical.Note to Practitioners—This study is stimulated by the need for optimizing the placement of Micro-PMU (µPMU) in distribution network. Since the new µPMU device DULR has the same relay protection function as FTU, and distributed generation can supply power to the island after failure, this paper adds the load loss rate to the constraint conditions to study the influence of fault reconstruction on the placement scheme. A new two-step SE method considering mixed measurements was used in this paper to improve the computational efficiency of real-time SE of large-scale system while ensuring the accuracy of the calculation results. We have conducted tests in IEEE-33 and IEEE-123 systems. After preliminary verification, compared with the single fault scenario, we find that the placement scheme considering multiple fault scenarios can effectively improve the accuracy of state estimation and reduce the load loss rate of each fault scenario and only increase the cost a little. The increase in the number of DG and contact lines in the network will also effectively improve the feasibility of the placement scheme. The increase of the number of FTU configurations can effectively reduce the configuration of DULR by adding a small amount of µPMU, reduce the total cost as a result. In future studies, we will further consider the integrated configuration of µPMU, DULR and FTU, to meet more failure scenarios while reducing costs.

Learning‐based tracking control of AUV: Mixed policy improvement and game‐based disturbance rejection

AbstractA mixed adaptive dynamic programming (ADP) scheme based on zero‐sum game theory is developed to address optimal control problems of autonomous underwater vehicle (AUV) systems subject to disturbances and safe constraints. By combining prior dynamic knowledge and actual sampled data, the proposed approach effectively mitigates the defect caused by the inaccurate dynamic model and significantly improves the training speed of the ADP algorithm. Initially, the dataset is enriched with sufficient reference data collected based on a nominal model without considering modelling bias. Also, the control object interacts with the real environment and continuously gathers adequate sampled data in the dataset. To comprehensively leverage the advantages of model‐based and model‐free methods during training, an adaptive tuning factor is introduced based on the dataset that possesses model‐referenced information and conforms to the distribution of the real‐world environment, which balances the influence of model‐based control law and data‐driven policy gradient on the direction of policy improvement. As a result, the proposed approach accelerates the learning speed compared to data‐driven methods, concurrently also enhancing the tracking performance in comparison to model‐based control methods. Moreover, the optimal control problem under disturbances is formulated as a zero‐sum game, and the actor‐critic‐disturbance framework is introduced to approximate the optimal control input, cost function, and disturbance policy, respectively. Furthermore, the convergence property of the proposed algorithm based on the value iteration method is analysed. Finally, an example of AUV path following based on the improved line‐of‐sight guidance is presented to demonstrate the effectiveness of the proposed method.

Techno-economic optimization and feasibility of PCM-based seasonal thermal energy storage systems for district heating and cooling

Phase change materials (PCM) are an attractive seasonal thermal energy storage solution for load shifting due to relatively high energy density. Nevertheless, the choice of the right design parameters, such as storage size and phase-change temperature, is nontrivial, as these are tightly linked to the expected seasonal operation of the storage. This paper presents a combined design and operation optimization framework for sizing PCM-based seasonal thermal storage, which can capture dynamic behaviour of the storage in sensible and latent phases, and its impact on the efficiency of connected heat pumps and chillers. The proposed method, formulated as a mixed integer quadratically-constrained programming problem, was applied to a case study of heating-dominated district. It was found that the optimal PCM melting temperature equals to the heating demand supply temperature, thus removing the need of a heat pump to discharge the storage. The optimal operation of storage requires a full charging and discharging cycle of both latent and liquid phase. Higher CO2 emission price does not lead to a significant reduction of CO2 emissions, but the storage size does, leading to a higher heating coverage ratio of the storage, and consequently CO2 emissions and cost savings, which can be further enhanced with PV integration. The economic analysis indicates that, unless other benefits such as storage volume reduction are accounted for, PCM cost should drop by a factor 4 to make this solution economically viable for seasonal storage.

Enhancing Cognitive Fit: Exploring the Potential of Mixed Reality for Developing Mental Rotation Skills

Mixed Reality is a promising venue for spatial ability training, allowing participants to engage in problem-solving through gesture-based interactions with holographic objects. 3-D measurement of learning in Mixed Reality environments may result in a better cognitive fit than 2-D. This mixed-method study measures and enhances mental rotation ability and investigates user experience in Mixed Reality. To assess mental rotation ability, we adapted the Purdue Spatial Visualization Test:Rotation for Microsoft HoloLens 2, creating a measurement tool for our Mixed Reality-based training program, Holomental. Comparing 2-D and 3-D tests, we explored how stimulus dimensionality influences accuracy and cognitive load. Our findings indicate that Holomental enhances mental rotation performance, both in 2-D and 3-D. Cognitive load in the 3-D test was lower than in the 2-D test. Semi-structured interviews revealed participants’ appreciation for the representational and interactional affordances of the training environment. This study provides valuable insights into the effectiveness of 3-D spatial training, with implications and suggestions for future design considerations.

A two-layer strategy for sustainable energy management of microgrid clusters with embedded energy storage system and demand-side flexibility provision

The intermittent nature of renewable energy generation and the fluctuating demands pose persistent challenges in microgrid operations. In response, stakeholders and operators have turned to clustering the geographically adjacent microgrids as a solution. In this context, this paper introduces a novel two-layer energy management strategy for microgrid clusters, utilizing demand-side flexibility and the capabilities of shared battery energy storage (SBES) to minimize operational costs and emissions, while ensuring a spinning reserve within individual microgrids to prevent load-shedding. In the lower layer, the proposed approach devises optimal day-ahead operation policies, while the upper layer employs a cooperative strategy to further optimize the operational efficiency across the entire cluster. The energy management problem is accurately formulated as a mixed integer quadratic programming (MIQP) optimization, which incorporates linear terms in the problem's constraints. The formulation accounts for operational costs associated with SBES including expenses of charging/discharging and changes in operating states (CiOS). Real-world case studies with a cluster of three microgrids in Australia validate the effectiveness of this approach. Results show a reduction in operational costs for the base case scenario by 6.96 % compared to conventional microgrid management strategies. Sensitivity analyses further demonstrate the economic benefits of varying SBES capacity and flexibility pricing, with savings ranging from 6.5 % to 8.1 %. The proposed strategy also reduces CO2 emissions by up to 11.6 %, while improving system reliability. This strategy holds promise for integration into distributed energy systems with high renewable penetration and clustered local grids, offering significant advantages for utility operators and end-users through improved energy efficiency and reduced emissions.