Search Results (5)

Chronic environmental exposure to toxic heavy metals, which often occurs as a mixture through occupational and industrial sources, has been implicated in various neurological disorders, including Parkinsonism. Vanadium pentoxide (V₂O₅) typically presents along with manganese (Mn), especially in welding rods and high-capacity batteries, including electric vehicle batteries; however, the neurotoxic effects of vanadium (V) and Mn co-exposure are largely unknown. In this study, we investigated the neurotoxic impact of MnCl₂, V₂O_5, and MnCl₂-V₂O₅ co-exposure in an animal model. C57BL/6 mice were intranasally administered either de-ionized water (vehicle), MnCl₂ (252 µg) alone, V₂O₅ (182 µg) alone, or a mixture of MnCl₂ (252 µg) and V₂O₅ (182 µg) three times a week for up to one month. Following exposure, we performed behavioral, neurochemical, and histological studies. Our results revealed dramatic decreases in olfactory bulb (OB) weight and levels of tyrosine hydroxylase, dopamine, and 3,4-dihydroxyphenylacetic acid in the treatment groups compared to the control group, with the Mn/V co-treatment group producing the most significant changes. Interestingly, increased levels of α-synuclein expression were observed in the substantia nigra (SN) of treated animals. Additionally, treatment groups exhibited locomotor deficits and olfactory dysfunction, with the co-treatment group producing the most severe deficits. The treatment groups exhibited increased levels of the oxidative stress marker 4-hydroxynonenal in the striatum and SN, as well as the upregulation of the pro-apoptotic protein PKCδ and accumulation of glomerular astroglia in the OB. The co-exposure of animals to Mn/V resulted in higher levels of these metals compared to other treatment groups. Taken together, our results suggest that co-exposure to Mn/V can adversely affect the olfactory and nigral systems. These results highlight the possible role of environmental metal mixtures in the etiology of Parkinsonism. Full article

Buildings are highly demanding of global energy consumption. Their functions, design, location, and other parameters influence the magnitude of such consumption. However, a key factor that can significantly change energy demand is the occupant’s interaction with the environment. It is, therefore, prudent to integrate the occupant profile within the six determinants of energy use, as proposed by the International Energy Agency. International standards propose an occupancy profile that has been implemented for design and performance analysis. However, these do not reflect reality, have little precision in their results, and affect occupant comfort and energy consumption expectations. To mitigate this problem, the literature proposes various methodologies to establish a mainly stochastic analysis offering optimal results. Panama, a country in the process of improving its energy matrix, finds it convenient to apply studies on the occupants’ behavior (OB) and preferences to guarantee comfort and avoid energy losses, supporting the purposes established in the National Energy Plan of Panama 2015–2050, guiding energy policy. This research seeks to define a particular pattern in occupants’ behavior in Panama through the analysis of surveys, identify its impact on energy consumption through dynamic simulation, and compare it with energy consumption generated by international standards. Results showed great differences in the energy consumption estimated via typical OB-based surveys and OB from standards, where the consumption by the latter can increase above 50%, while with surveys, this differs from the reference by no more than 11%. Full article

Occupant behavior (OB) has a significant impact on household air-conditioner (AC) energy use. In recent years, bottom-up simulation coupled with stochastic OB modeling has been intensively developed for estimating residential AC consumption. However, a comprehensive analysis of the diverse behavioral preference patterns of occupants regarding AC use is hampered by the limited availability of large-scale residential energy demand data. Therefore, this study aimed to develop a prediction model for the residential household’s AC usage considering various OB-related diversity patterns based on monitoring data of appliance-level electricity use in a residential community of 586 households in Osaka, Japan. First, individual operation schedules and thermal preferences were identified and quantitatively extracted as the two main factors for the diverse behaviors across the whole community. Then, a clustering analysis classified the target households, finding four typical patterns for schedule preferences and three typical patterns for thermal preferences. These results were used, with time and meteorological data in the summer seasons of 2013 and 2014, as inputs for the proposed prediction model using Extreme Gradient Boosting (XGBoost). The optimized XGBoost model showed a satisfactory prediction performance for the on/off state in the testing dataset, with an F1 score of 0.80 and an Area under the Receiver Operating Characteristic (ROC) Curve (AUC) of 0.845. Full article

Commercial prototype building models were developed by the United States Department of Energy (DOE) to analyze the energy savings of the ASHRAE 90.1 standard. However, in the DOE models, occupant behavior inputs were deterministic and the stochasticity of occupant behavior was not fully characterized. This study evaluated the impacts of stochastic occupant behavior on building energy consumption and energy savings analysis from upgrading the ASHRAE 90.1-2016 to 2019 in sixteen climate zones in the United States (U.S.). Three occupant behavior styles (austerity, normal, and wasteful) were defined to represent the different levels of energy consciousness. The DOE medium office prototype models were used as the baseline (normal behavior style). The occupant behavior functional mock-up unit (obFMU) was used to model the stochastic occupant behavior models (austerity and wasteful). The EnergyPlus medium office prototype models were modified to co-simulate with the obFMU models. The results of 16 climate zones were aggregated by the relative construction volume of each climate zone. The results showed that the weighted national annual source energy use intensity (EUI) of the austerity, normal, and wasteful behavior styles were 203.81 kWh/m², 287.15 kWh/m², and 388.33 kWh/m² for ASHRAE 90.1-2016, and 192.43 kWh/m², 273.48 kWh/m², and 371.28 kWh/m² for ASHRAE 90.1-2019, respectively. Compared to the normal behavior style, the austerity behavior style consumed 29% less source energy, while the wasteful behavior style consumed 36% more source energy. From upgrading the ASHRAE 90.1-2016 to 2019, the energy saving percentages based on the austerity, normal, and wasteful behavior styles were 5.59%, 4.78%, and 4.42%, respectively. The stochastic occupant behavior significantly impacted the building energy consumption, and their impacts on the energy savings analysis of upgrading ASHRAE 90.1 were also not negligible. Full article

Current research is focused on sensing and modeling occupant behavior to predict it and automate building controls. Another line of research recommends influencing the behavior of occupants through feedback mechanisms and engagement. Yet, most of the work has focused on pushing occupants to reduce energy consumption over a long time and does not explore the potential to guide users to take specific actions promptly. The study examines a new interface mechanism that aims to solicit immediate and predefined actions from occupants. Building on seminal research in the field, the study uses art visualization to reinterpret social feedback. We test this approach in an immersive interaction space where participants react to artistic visuals to attain predefined settings for three indoor devices. In the 197 interactions recorded, participants’ overall actions conformed with the predefined goals. The participants were able to reach all or some of the targets in more than 80%, within an average of less than 30 seconds. We also see that complementing the visuals with textual hints improved the interaction in terms of engagement and accuracy. We conclude that ambient, abstract, and artistic real-time goal-driven feedback is effective in influencing immediate actions. We recommend that guiding occupants didactically has a strong potential for advancing building controls. Full article