From domestic energy demand to household activity patterns

Residential building energy usage can be considered as being derived from the activity patterns of individuals inside the home. As such an activity-based energy demand model that can create in-home energy usage profiles from household activity patterns is the key to a better building energy demand analysis. In order to find the relation between building energy usage and activity profiles, energy usage data with an overlapping activity diary survey is needed. However, there is no detailed data containing information on both household activity schedules and energy usage. Therefore, utilizing a Bayesian approach, we explore the possibility of reverse engineering to get the household activity patterns from energy usage profiles. The findings can be further used for linking the domestic energy demand to the activity schedules of the occupants

Integrated in- and out-of-home scheduling framework: A utility optimization-based approach

Existing activity-based modeling predominantly focus on out-of-home activities in order to understand transport demand. In this research, we extend the state of practice in activity-based modelling by determining both in- and out-of-home activities in a single scheduling framework. This approach has two main benefits and applications: Firstly, it can capture the trade-offs between in-home and out-of-home activities. Secondly, in-home time-use patterns can be used to model high resolution energy demand, which can contribute to demand side management. Our work builds on an existing optimisation framework, which treats individuals as maximising their total utility from completed activities and incorporates multiple scheduling decisions simultaneously. The framework has been extended to determine the choice of location for activities such as work, study, and leisure. The approach is tested on a set of detailed daily schedules extracted from the 2016-2020 UK Time Use Survey data. The results show that the model is able to generate peoples’ daily activity schedules based on their preferences and constraints

Simulating intra-household interactions for in- and out-of-home activity scheduling

Various interactions, time arrangements, and constraints exist for individuals scheduling their day as a member of a household, which affect their in-home as well as out-of-home activity schedule. However, the existing activity-based models are mostly based on the individual decision-making process, which are limited in their demonstration of behaviour. We simulate multiple intra-household interaction dimensions within the same framework and capture the coordination of the activity scheduling decisions among all household members. Our approach adopts the Optimisation-based Activity Scheduling Integrating Simultaneous choice dimensions (OASIS) framework, which is at the level of isolated individuals and focuses on out-of-home activity schedules. We jointly simulate in- and out-of-home activities and incorporate interactions into the framework. Our framework contributes to the state-of-the-art in activity-based modelling by explicitly capturing multiple interactions within the same model, such as the allocation of the private vehicle to household members, dividing household maintenance responsibilities, escorting, joint activity participation, and sharing rides. We operationalise the model using time-use-survey data from the United Kingdom. The simulation results demonstrate the ability of the framework to capture complex intra-household interactions. We then demonstrate how these interactions can cause individuals to deviate from their schedules planned in isolation. This is a general framework applicable to different household compositions and available resources

Integrated in- and out-of-home scheduling framework: A utility optimization-based approach

Existing activity-based modeling predominantly focus on out-of-home activities in order to understand transport demand. In this research, we extend the state of practice in activity-based modelling by determining both in- and out-of-home activities in a single scheduling framework. This approach has two main benefits: Firstly, it can capture the trade-offs between in-home and out-of-home activities. Secondly, in-home time-use patterns can be used to model high resolution energy demand. Our work builds on an existing optimisation framework, which treats individuals as maximising their total utility from completed activities and incorporates multiple scheduling decisions simultaneously. The approach is tested on a set of detailed daily schedules extracted from the the 2016-2020 UK Time Use Survey data. The results show that the model is able to generate peoples’ daily activity schedules based on their individual preferences and constraints

Integrated models of transport and energy demand: A literature review and framework

Energy and transport demand can both be considered as being derived from an individual’s activity participation. As such, both energy and transport demand are inherently linked: completing activities inside the home generates residential energy demand, where completing activities outside the home generates transportation and non-residential energy demand. Whilst there are several works in the literature that focus on either energy or transportation demand, there remain very few studies which explicitly investigate their interaction. To address this need, in this paper we conduct in-depth literature review of transportation and energy demand modeling. The review analyses the methodologies employed within each domain in order to (a) establish the state-of-research for energy demand modeling and (b) identify the suitable opportunities for joining these two domains. Drawing on a review of the current papers, we identify four key areas of practice: (i) activity scheduling, (ii) building energy demand, (iii) transportation energy demand, and (iv) the integration of components. Finally, based on the findings from the review, we propose a new framework for joint building and transportation energy demand modeling at an urban scale

Evaluating Discrimination Indexes for Iron Deficiency Anemia among Children Aged Between 1-15 Years Old

Background: Iron Deficiency Anemia (IDA) is a massive health concern with a high frequency in Iran. Differentiating between IDA and other microcytic-hypochromic anemia like beta thalassemia minor requires demanding and money consuming tests. That is why this study aimed to assess well-suited and conclusive deferential indexes for IDA diagnosis among children aged between 1-15 years old Methods: Blood samples were collected from outpatients aged between 1-15 years old. Consequently, Ferritin, Hemoglobin, Serum Iron, RBC count, mean corpuscular volume (MCV), mean corpuscular hemoglobin (MCH), red cell volume distribution width (RDW), total iron binding capacity (TIBC) were determined. Furthermore, differential indexes including Mentzer, Shine and Lal and England-Frazer were measured and the data were analyzed using SPSS. Results: Out of 100 children, 72 individuals were healthy and 28 had IDA. The average age was 3.6±2.9 years. The prediction value of the RBC indexes for the differentiation IDA were as follows: MCV (99%), HB (96%), Ferritin (95%), HCT (87%), MCH (79%), Serum Iron (71%), RBC count (51%), RDW (27%), and TIBC (26%). The prediction values of the formulas were as follows: Shine and Lal (96%), Mentzer (80%), and England-Frazer (79%). Conclusion: According to the findings, it is possible to diagnose IDA by Complete Blood Count (CBC) test accompanied by differential indexes. A simple selective index such as Shine and Lal might be very beneficial for screening of IDA. This index is also useful for the diagnosis of microcytic anemia

Natural specific T cell immunity in patients with B-cell chronic lymphocytic leukaemia (B-CLL) : (A clinical and immunological study)

Analysis of TCRBV (T-cell receptor B variable) gene usage of the T cell repertoire in patients with B cell chronic lymphocytic leukaemia (B-CLL) and age-matched healthy control donors showed that major perturbations were more frequently seen in the CD4+ T cell subset than in CD8 population. Analysis of the CDR3 length polymorphism revealed a significantly higher degree of clonality within the CD4+ and CD8+ T cell repertoire of patients as compared to the normal control population. These results suggest that non-malignant CD4+ T cells as well as CD8+ T cells may be involved in the pathogenesis of B-CLL. CLL patients showed the presence of a naturally occurring CD4 and CD8 T cell specifically recognizing the leukaemic B cells. Analyses of cytokines by realtime RT-PCR revealed that Thl cytokines were the most frequently observed cytokines expressed by T cells recognizing the autologous tumor B cells. Upregulation of CD80 on the leukaemic B cells was necessary for induction of the specific T cell response. The T cell response was either MHC class I- or class II-restricted. Analyses of TCR BV gene usage of tumor-restricted T cells showed overexpression 'of certain BVs in CD4 and CD8 T cells as compared to native T cells. Furthermore, analysis of the CDR3 length polymorphism showed that over-expressed BVs shifted from mostly a polyclonal pattern to an oligoclonal/monoclonal pattern after stimulation of T cells with the autologous tumor B cells. Dendritic cells (DC) were generated in vitro from blood CD14+ cells. Most of the DC exhibited a mature phenotype indicated by CD83 and MHC class II expression, as well as by morphology. CLL DC had a similar expression of accessory molecules as control DC. However the pattern of cytokines was different in CLL as compared to control DC. DC of CLL patients had a similar capacity to present antigen as control DC. A VH-CDR3 specific T cell response was demonstrated in CLL patients both by proliferation assay and by IFN-gamma production. The T cell specific response could be inhibited by monoclonal antibodies against MHC class Il or MHC class I molecules. In summary, in B CLL patients a natural specific T cell response can be demonstrated. However, the biological significance of such a tumor specific immunity remains to be established. The occurrence of leukaemia specific T cells suggests that CLL might a candidate for developing a therapeutic vaccine approach