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Abstract Animals often display choice bias, or a preference for one option over the others, which can significantly impede learning new tasks. Delayed match-to-sample (DMS) tasks with two-alternative choices of lickports on the left and right have been widely used to study sensory processing, working memory, and associative memory in head-fixed animals. However, extensive training time, primarily due to the animals' biased licking responses, limits their practical utility. Here, we present the implementation of an automated side bias correction system in an olfactory DMS task, where the lickport positions and the ratio of left- and right-rewarded trials are dynamically adjusted to counterbalance mouse’s biased licking responses during training. The correction algorithm moves the preferred lickport farther away from the mouse’s mouth and the non-preferred lickport closer, while also increasing the proportion of non-preferred side trials when biased licking occurs. We found that adjusting lickport distances and the proportions of left- versus right-rewarded trials effectively reduces the mouse’s side bias. Further analyses reveal that these adjustments also correlate with subsequent improvements in behavioral performance. Our findings suggest that the automated side bias correction system is a valuable tool for enhancing the applicability of behavioral tasks involving two-alternative lickport choices.

Recently, there has been a growing interest in sustainable agricultural methods aimed at reducing energy consumption and mitigating environmental impacts. Among these methods, the integration of rooftop greenhouses into buildings has emerged as a promising solution for urban agriculture, offering various advantages such as energy-saving effects on both the host building and the rooftop greenhouse, improved resource use efficiency, enhanced food security, and reduced environmental impacts. However, there has been limited research on the energy-saving impact of rooftop greenhouses under different conditions and detailed heat transfer analysis based on actual buildings and rooftop greenhouses. The objective of this study is to investigate the energy benefits of building-integrated rooftop greenhouses by evaluating various operating scenarios for both the building and the greenhouse. A container and upper rooftop greenhouse structure were constructed, and building energy simulation models for the target system were developed. Four different operating scenarios for the greenhouse and three different operating scenarios for the building were compared. Depending on the operating scenarios, the total energy loads of the container and RTG were reduced by 18.4% to 24.7% and 0.7% to 6.3%, respectively. The findings of this study can be utilized for the development of optimized greenhouse control strategies.

In the context of increasing energy demands and the integration of renewable energy sources, this review focuses on recent advancements in energy storage control strategies from 2016 to the present, evaluating both experimental and simulation studies at component, system, building, and district scales. Out of 426 papers screened, 147 were assessed for eligibility, with 56 included in the final review. As a first outcome, this work proposes a novel classification and taxonomy update for advanced storage control systems, aiming to bridge the gap between theoretical research and practical implementation. Furthermore, the study emphasizes experimental case studies, moving beyond numerical analyses to provide practical insights. It investigates how the literature on energy storage is enhancing building flexibility and resilience, highlighting the application of advanced algorithms and artificial intelligence methods and their impact on energy and financial savings. By exploring the correlation between control algorithms and the resulting benefits, this review provides a comprehensive analysis of the current state and future perspectives of energy storage control in smart grids and buildings.

Abstract Animals tend to alternate between different choices, which requires the ability to remember recent choices. The Y-maze spontaneous alternation test is widely used in various animal models for assessing short-term memory, and its precise evaluation depends upon the accurate determination of the arm visit sequence. However, an objective method for defining arm visits is lacking owing to uncertainty regarding the extent to which an animal must go into the arm to be considered visited. Here, we conducted quantitative analyses on mice behavior in the Y-maze while systematically varying the arm visit threshold and assessed the effect of acute social isolation on spatial working memory. Our results revealed that 24-h social isolation significantly reduced spontaneous alternation rate when the arm threshold was set at the distal part of the arm. Furthermore, the memory of the recently visited arms faded away faster in the socially isolated mice. However, other behavioral factors were comparable to those of the group-housed mice, indicating a specific impairment of short-term memory. Our findings suggest that the location of arm visit threshold is critical for the precise evaluation of short-term memory, and our study provides a method for comprehensively and systematically assessing spontaneous alternation behavior in the Y-maze.

Abstract Recognizing an individual and retrieving and updating the value information assigned to the individual are fundamental abilities for establishing social relationships. To understand the neural mechanisms underlying the association between social identity and reward value, we developed Go-NoGo social discrimination paradigms that required male subject mice to distinguish between familiar mice based on their individually unique characteristics and associate them with reward availability. We found that mice could discriminate individual conspecifics through a brief nose-to-nose investigation, and this ability depended on the dorsal hippocampus. Two-photon calcium imaging revealed that dorsal CA1 hippocampal neurons represented reward expectation during social, but not non-social tasks, and these activities were maintained over days regardless of the identity of the associated mouse. Furthermore, a dynamically changing subset of hippocampal CA1 neurons discriminated between individual mice with high accuracy. Our findings suggest that the neuronal activities in CA1 provide possible neural substrates for associative social memory.

Mobility hubs are interconnected nodes where several travel modes, private or public, are integrated. They aim to ensure an efficient inter-modality and to prioritize sustainable transportation. Determining their best location is a new fertile research area attracting considerable attention. Although past studies have addressed the location conundrum using the hub location problem (HLP) models, much of the literature has overlooked the aspect of social equity. In this context, social equity refers to the distribution of advantages and disadvantages of a particular policy across diverse social strata, avoiding any social exclusion and discrimination. This study intends to select mobility hub locations that achieve balanced social justice and optimal coverage. It adopted the single allocation ??-median hub with a fixed cost model, where the fixed cost encapsulated equity and coverage indices. For equity, the Gini index was derived using social quantile group data. The meta-heuristic method Genetic Algorithm was exploited to solve the HLP optimization. This model displayed a good performance with a high fitness value of around 7.7e7, selecting nine (9) districts. Results of the first optimization step di underscored that locating mobility hubs within mixed land-use areas inhabited or frequented by low to medium-income strata helps promote equitable access and social justice while enhancing sustainable transportation ridership and coverage.

Summary: Social and reward signal processing and their association are critical elements of social motivation. Despite the use of reward learning to improve the social interactions of patients with autism spectrum disorder (ASD), the underlying neural mechanisms are unknown. Here, we found different yet conjunct neuronal representations of social and reward signals in the mouse medial prefrontal cortex (mPFC). We also found that social signal processing is selectively disrupted, whereas reward signal processing is intact in the mPFC of Shank2-knockout mice, a mouse model of ASD. Furthermore, reward learning not only allows Shank2-knockout mice to associate social stimuli with reward availability, but it also rescues the impaired social signal processing. These findings provide insights into the neural basis for the therapeutic use of reward learning in ASD.

The Republic of Korea was ranked 11th globally, in 2018, in terms of greenhouse gas emissions, of which the transportation sector contribution was estimated to be 14 % in 2017. Many policies have been drawn to enhance transport sustainability and reduce its emissions. According to the Climate Action Tracker (CAT), the policies and actions of South Korea to achieve the goal set in the Paris Agreement, are highly insufficient. Also, the environmental community in Korea has claimed the weakness of the 2017 emissions strategy. To increase policies’ efficiency an investigation of the drivers behind greenhouse gases needs to be considered. This paper is decomposing both overall greenhouse gases and transport sector greenhouse gases, to analyse the effect of economic growth, energy intensity, energy mix, technology, urbanization, R&D expenditure, and population. The LMDI results showed that GDP, R&D expenditure, and energy consumption have a strong effect on increasing carbon emissions. While population and urbanization factors have a weak effect for the analysis period 2003-2016, due to the stable urbanization and population rate within the period. The significant contribution of R&D expenditure in increasing GHG emissions showed an urgent need to revise the R&D investment to boost non-carbon transportation research. Additionally, the energy structure effect was not significant, as the reliance on fossil fuel is high despite the efforts to reduce it. This revealed that the adopted fuel policies need strengthening measures and continuous improvement. The study deduced the vital need to raise the use of renewable and non-carbon energy, to strengthen sustainable transportation policies and investments, with a focus on public transportation modes, and finally to establish a good environment for a vigorous system for the implementation and enhancement of active modes.

Abstract The development of a distributed heat pump system that utilizes several renewable energy sources to meet building heating and cooling demands was reported in this paper. We refer to this system as the multiple‐source and multiple‐use heat pump (MMHP) system. A unique sky source heat pump, ground heat exchangers, and various heat pumps are connected through closed‐loop piping system within a building. This kind of configuration enables improved matching of supply and demand which offers a high flexibility. The winter and summer field testing are conducted to investigate the system performance using a testing building.

Group I metabotropic glutamate receptors (group I mGluRs; mGluR1 and mGluR5) exert diverse effects on neuronal and synaptic functions, many of which are regulated by intracellular Ca(2+). In this study, we characterized the cellular mechanisms underlying Ca(2+) mobilization induced by (RS)-3,5-dihydroxyphenylglycine (DHPG; a specific group I mGluR agonist) in the somata of acutely dissociated rat hippocampal neurons using microfluorometry. We found that DHPG activates mGluR5 to mobilize intracellular Ca(2+) from ryanodine-sensitive stores via cyclic adenosine diphosphate ribose (cADPR), while the PLC/IP(3) signaling pathway was not involved in Ca(2+) mobilization. The application of glutamate, which depolarized the membrane potential by 28.5±4.9 mV (n = 4), led to transient Ca(2+) mobilization by mGluR5 and Ca(2+) influx through L-type Ca(2+) channels. We found no evidence that mGluR5-mediated Ca(2+) release and Ca(2+) influx through L-type Ca(2+) channels interact to generate supralinear Ca(2+) transients. Our study provides novel insights into the mechanisms of intracellular Ca(2+) mobilization by mGluR5 in the somata of hippocampal neurons.

The article discusses research on the development of a novel digital implant scanning strategy which aims to improve accuracy of scanbody alignments. Topics explored include the compatibility of the procedure with computer-aided design (CAD) and computer-aided manufacturing (CAM) technologies, the modification of the scanbody library to minimize errors in scanbody matching, and the need to determine the accurate positioning of dental implant fixtures.

Mobility hubs are interconnected nodes where several travel modes, private or public, are integrated. They aim to ensure an efficient inter-modality and to prioritize sustainable transportation. Determining their best location is a new fertile research area attracting considerable attention. Although past studies have addressed the location conundrum using the hub location problem (HLP) models, much of the literature has overlooked the aspect of social equity. In this context, social equity refers to the distribution of advantages and disadvantages of a particular policy across diverse social strata, avoiding any social exclusion and discrimination. This study intends to select mobility hub locations that achieve balanced social justice and optimal coverage. It adopted the single allocation p -median hub with a fixed cost model, where the fixed cost encapsulated equity and coverage indices. For equity, the Gini index was derived using social quantile group data. The meta-heuristic method Genetic Algorithm was exploited to solve the HLP optimization. This model displayed a good performance with a high fitness value of around 7.7e7, selecting nine (9) districts. Results of the first optimization step di underscored that locating mobility hubs within mixed land-use areas inhabited or frequented by low to medium-income strata helps promote equitable access and social justice while enhancing sustainable transportation ridership and coverage. [ABSTRACT FROM AUTHOR]

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Currently, 3D printers, especially digital light processing (DLP) printers, are widely used in clinical dentistry. However, due to the shrinkage property of resin, their accuracy is not optimal for full-arch dental model printing. To overcome these limitations, fused deposition modeling (FDM) with filament that undergoes minimum shrinkage was introduced. Accordingly, a combination of FDM printing with the specific tooth die output of DLP printing for the full-arch dental model is proposed in the present report. [ABSTRACT FROM AUTHOR]

The Republic of Korea was ranked 11th globally, in 2018, in terms of greenhouse gas emissions, of which the transportation sector contribution was estimated to be 14 % in 2017. Many policies have been drawn to enhance transport sustainability and reduce its emissions. According to the Climate Action Tracker (CAT), the policies and actions of South Korea to achieve the goal set in the Paris Agreement, are highly insufficient. Also, the environmental community in Korea has claimed the weakness of the 2017 emissions strategy. To increase policies' efficiency an investigation of the drivers behind greenhouse gases needs to be considered. This paper is decomposing both overall greenhouse gases and transport sector greenhouse gases, to analyse the effect of economic growth, energy intensity, energy mix, technology, urbanization, R&D expenditure, and population. The LMDI results showed that GDP, R&D expenditure, and energy consumption have a strong effect on increasing carbon emissions. While population and urbanization factors have a weak effect for the analysis period 2003-2016, due to the stable urbanization and population rate within the period. The significant contribution of R&D expenditure in increasing GHG emissions showed an urgent need to revise the R&D investment to boost non-carbon transportation research. Additionally, the energy structure effect was not significant, as the reliance on fossil fuel is high despite the efforts to reduce it. This revealed that the adopted fuel policies need strengthening measures and continuous improvement. The study deduced the vital need to raise the use of renewable and non-carbon energy, to strengthen sustainable transportation policies and investments, with a focus on public transportation modes, and finally to establish a good environment for a vigorous system for the implementation and enhancement of active modes. [ABSTRACT FROM AUTHOR]