Job Selection in a Network of Autonomous UAVs for Delivery of Goods

This article analyzes two classes of job selection policies that control how a network of autonomous aerial vehicles delivers goods from depots to customers. Customer requests (jobs) occur according to a spatio-temporal stochastic process not known by the system. If job selection uses a policy in which the first job (FJ) is served first, the system may collapse to instability by removing just one vehicle. Policies that serve the nearest job (NJ) first show such threshold behavior only in some settings and can be implemented in a distributed manner. The timing of job selection has significant impact on delivery time and stability for NJ while it has no impact for FJ. Based on these findings we introduce a methodological approach for decision-making support to set up and operate such a system, taking into account the trade-off between monetary cost and service quality. In particular, we compute a lower bound for the infrastructure expenditure required to achieve a certain expected delivery time. The approach includes three time horizons: long-term decisions on the number of depots to deploy in the service area, mid-term decisions on the number of vehicles to use, and short-term decisions on the policy to operate the vehicles

Sandstone intrusions along different types of faults and their effect on fluid flow in siliciclastic reservoirs

We are very grateful to companies sponsoring Phase 3 of the Sand InjectionResearch Group (SIRG). We acknowledge the continuing help provided by the Bureau of Land Management (BLM) in California.Peer reviewedPostprin

Linguistic sleuthing for innovators

For centuries “innovation” has been a topic of book authors and academic researchers as documented by Ngram and Google Scholar search results. In contrast, “innovators” have had substantially less attention in both the popular domain and the academic domain. The purpose of this paper is to introduce a text analysis research methodology to linguistically identify “innovators” and “non-innovators” using Hebert F. Crovitz’s 42 relational words. Specifically, we demonstrate how to combine the use of two complementary text analysis software programs: Linguistic Inquiry and Word Count and WORDij to simply count the percent of use of these relational words and determine the statistical difference in use between “innovators” and “non-innovators.” We call this the “Crovitz Innovator Identification Method” in honor of Herbert F. Crovitz, who envisioned the possibility of using a small group of 42 words to signal “innovation” language. The Crovitz Innovator Identification Method is inexpensive, fast, scalable, and ready to be applied by others using this example as their guide. Nevertheless, this method does not confirm the viability of any innovation being created, used or implemented; it simply detects how a person’s language signals innovative thinking. We invite other scholars to join us in this linguistic sleuthing for innovators

Forecasting consumer confidence through semantic network analysis of online news

This research studies the impact of online news on social and economic consumer perceptions through semantic network analysis. Using over 1.8 million online articles on Italian media covering four years, we calculate the semantic importance of specific economic-related keywords to see if words appearing in the articles could anticipate consumers' judgments about the economic situation and the Consumer Confidence Index. We use an innovative approach to analyze big textual data, combining methods and tools of text mining and social network analysis. Results show a strong predictive power for the judgments about the current households and national situation. Our indicator offers a complementary approach to estimating consumer confidence, lessening the limitations of traditional survey-based methods

Petrofacies of Eocene sand injectites of the Tumey Giant Injection Complex, California (USA)

The authors gratefully acknowledge support from Shell Brazil and CNPq through the “BG05: UoA-UFRGS-SWB Sedimentary Systems” project at UFRGS and UoA and the strategic importance of the support given by ANP through the R&D levy regulation. We thank all the support from the Sand Injection Research Group (SIRG). We also wish to thank the support of the Bureau of Land Management (CA - USA) providing legal access to the study area.Peer reviewedPostprin

Predominant Golgi-residency of the plant K/HDEL receptor is essential for its function in mediating ER retention

Accumulation of soluble proteins in the endoplasmic reticulum (ER) of plants is mediated by a receptor termed ER RETENTION DEFECTIVE 2 (ERD2) or K/HDEL receptor. Using two gain-of-function assays and by complementing loss of function in Nicotiana benthamiana we discovered that compromising the lumenal N-terminus or the cytosolic C-terminus with fluorescent fusions abolishes its biological function and profoundly affects its subcellular localization. Based on the confirmed asymmetrical topology of ERD2 we engineered a new fluorescent ERD2 fusion protein that retains biological activity. Using this fusion, we show that ERD2 is exclusively detected at the Golgi apparatus, unlike non-functional C-terminal fusions which also label the ER. Moreover, ERD2 is confined to early Golgi compartments and does not show ligand-induced redistribution to the ER. We show that the cytosolic C-terminus of ERD2 plays a crucial role in its function. Two conserved Leucine residues that do not correspond to any known targeting motifs for ER-Golgi trafficking were shown to be essential for both ERD2 Golgi residency and its ability to mediate ER retention of soluble ligands. The results suggest that anterograde ER to Golgi transport of ERD2 is either extremely fast, well in excess of the bulk flow rate, or that ERD2 does not recycle in the way originally proposed

Boosting advice and knowledge sharing among healthcare professionals

Purpose: This study investigates the dynamics of knowledge sharing in healthcare, exploring some of the factors that are more likely to influence the evolution of idea sharing and advice seeking in healthcare. Design/methodology/approach: We engaged 50 pediatricians representing many subspecialties at a mid-size US children's hospital using a social network survey to map and measure advice seeking and idea sharing networks. Through the application of Stochastic Actor-Oriented Models, we compared the structure of the two networks prior to a leadership program and eight weeks post conclusion. Findings: Our models indicate that healthcare professionals carefully and intentionally choose with whom they share ideas and from whom to seek advice. The process is fluid, non-hierarchical and open to changing partners. Significant transitivity effects indicate that the processes of knowledge sharing can be supported by mediation and brokerage. Originality: Hospital administrators can use this method to assess knowledge-sharing dynamics, design and evaluate professional development initiatives, and promote new organizational structures that break down communication silos. Our work contributes to the literature on knowledge sharing in healthcare by adopting a social network approach, going beyond the dyadic level, and assessing the indirect influence of peers' relationships on individual networks

A leaf area index data set acquired in Sahelian rangelands of Gourma in Mali over the 2005–2017 period

The leaf area index of Sahelian rangelands and related variables such as the vegetation cover fraction, the fraction of absorbed photosynthetically active radiation and the clumping index were measured between 2005 and 2017 in the Gourma region of northern Mali. These variables, known as climate essential variables, were derived from the acquisition and the processing of hemispherical photographs taken along 1&thinsp;km linear sampling transects for five contrasted canopies and one millet field. The same sampling protocol was applied in a seasonally inundated Acacia open forest, along a 0.5&thinsp;km transect, by taking photographs of the understorey and the tree canopy. These observations collected over more than a decade, in a remote and not very accessible region, provide a relevant and unique data set that can be used for a better understanding of the Sahelian vegetation response to the current rainfall changes. The collected data can also be used for satellite product evaluation and land surface model development and validation. This paper aims to present the field work that was carried out during 13 successive rainy seasons, the measured vegetation variables, and the associated open database. Finally, a few examples of data use are shown. DOI of the referenced data set: https://doi.org/10.17178/AMMA-CATCH.CE.Veg_Gh.</p