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Stress hormone signaling via the glucocorticoid receptor (GR) modulates vulnerability to stress-related disorders, but whether GR influences how the brain encodes contextual experience is unknown. Mice with lifelong GR overexpression in forebrain glutamatergic neurons (GRov) show increased sensitivity to environmental stimuli. This phenotype is developmentally programmed and associated with profound changes in hippocampal gene expression. We hypothesized that GR overexpression influences hippocampal encoding of experiences. To test our hypothesis, we performed in vivo microendoscopic calcium imaging of 1359 dorsal CA1 pyramidal cells in freely behaving male and female WT and GRov mice during exploration of a novel open field. We compared calcium amplitude and event rate as well as sensitivity to center location and mobility between genotypes. GRov neurons exhibited higher average calcium activity than WT neurons in the novel open field. While most neurons showed sensitivity to center location and/or mobility, GRov neurons were more likely to be sensitive to center location and less likely to be sensitive to mobility, as compared to WT neurons. More than one-third of behavior-selective GRov neurons were uniquely sensitive to location without mobility sensitivity; these uniquely center-sensitive neurons were rare in WT. We conclude that dorsal CA1 pyramidal cells in GRov mice show increased activity in a novel environment and preferentially encode emotionally salient behavior. This heightened sensitivity to a novel environment and preferential encoding of emotionally salient elements of experience could underlie differential stress vulnerability in humans with increased glucocorticoid sensitivity.

Objective. To identify factors affecting compliance with follow-up during treatment in confirmed malaria patients at two health centers in Haiti. Methods. A prospective observational study of malaria patients undergoing treatment over a six-week period. Patients’ return visits (follow-up visits) to the health centers for consultation in accordance with the physicians’ requests were recorded and used to determine compliance. Socioeconomic data were obtained from patient enrollment questionnaires and through post-treatment interviews. The management practices and procedures at the health centers to retain patients were also reviewed. Descriptive statistics and Spearman’s rank correlation were used to identify significant factors, which were used as variables in a logistic regression model. Results. Sixty-eight percent of the malaria patients completed follow-up, with higher compliance being recorded in the larger, more established health center of Leogane (67%) than Cite Soleil (33%). The patient socioeconomic profiles differed between the two health center locations by level of education, religious diversity, household size, and percentage of married individuals. Crude logistic regression analyses identified health center location (OR = 0.179 [95% CI 0.064, 0.504]) and household size (OR = 1.374 [95% CI 1.056, 1.787]) to be associated with compliance. The adjusted model only identified health center location (OR = 0.226 [95% CI 0.056, 0.918]) as significantly associated with compliance. Conclusion. Although patients’ household size may be important according to the crude logistic regression analysis, in the adjusted analysis the site location of the health center where patients receive treatment was identified as the only important factor associated with follow-up compliance in malaria patients during treatment in Haiti. This information might be helpful to improve treatment outcomes and contribute to the monitoring of antimalarial resistance in Haiti.

Customer clustering technology for distribution process is widely used in location selection, distribution route optimization and vehicle scheduling optimization of power logistics distribution center. Aiming at the problem of customer clustering with unknown distribution center location, this paper proposes a clustering algorithm considering distribution network structure and distribution volume constraint, which makes up for the defect that the classical Euclidean distance does not consider the distribution road information. This paper proposes a logistics distribution customer clustering algorithm, which improves CLARANS algorithm to make the clustering results meet the constraints of customer distribution volume. By using the single vehicle load rate, the sufficient conditions for logistics distribution customer clustering to be solvable under the condition of considering the ubiquitous and constraints are given, which effectively solves the problem of logistics distribution customer clustering with sum constraints. The results state clearly that the clustering algorithm can effectively deal with large-scale spatial data sets, and the clustering process is not affected by isolated customers, The clustering results can be effectively applied to the distribution center location, distribution cost optimization, distribution route optimization and distribution area division of vehicle scheduling optimization.

Abstract Standard field architecture is generally based on topsides production and distribution of power and chemicals necessary to operate equipment in drill centers. The paper will present efficient field architectures adapted to operate remote tie-backs with different combinations of subsea electrical power distribution, remote power generation and storage, and improved ways to mitigate corrosion, hydrates and wax issues for long tie-backs. Developing remote resources requires several technology bricks that enable a cost effective and reliable technical solution. To reduce the CAPEX, the main objective is to reduce the number of tubes typically with one single heated flowline to avoid a long and costly service line or with one small power cable and local distribution of power to avoid a heavy and expensive large umbilical. Alternatively, power can be generated and stored at drill center location and chemicals can also be managed locally with limited OPEX. A significant focus was done recently on technology developments enabling long distance tie-back developments. Domain of application and interest of each technology is generally well known and the delivered value is well presented. Looking for the most appropriate combination of technologies on a new field development is now the new challenge to figure out new opportunities. This paper proposes to group the long distance tie-backs fields in three main categories based on extensive studies done for several operators and to present the best architecture for each category. The first category groups very long distance single end tie-backs for which a cold flow system combined with full electrical equipment at drill center location is adapted. The second one is applicable for more consequent development where several drill centers are combined to one long and heated export line; with subsea electrical distribution to power each branch of the remote field and local management of chemicals at each drill center. The third category groups all daisy chain developments for which a heated line gathers the production coming from each fully electrical drill center. Each field development can generally be categorized in one out of the three categories presented in this paper. Based on this categorization, the right combination of low carbon and reliable new technologies enables valuable development of long tie-backs and then increases utilization area of each existing asset.