Crystal structure and spectroscopic characterization of a cobalt(II) tetraazamacrocycle: completing a series of first-row transition-metal complexes

The tetraazamacrocyclic ligand 1,4,8,11-tetramethyl-1,4,8,11-tetraazacyclotetra-decane (TMC) has been used to bind a variety of first-row transition metals but to date the crystal structure of the cobalt(II) complex has been missing from this series. The missing cobalt complex chlorido(1,4,8,11-tetramethyl-1,4,8,11-tetraazacyclotetradecane-κ^4N)cobalt(II) chloride dihydrate, [CoCl(C_(14)H_(32)N_4)]Cl·2H_2O or [Co^(II)Cl(TMC)]Cl·2H_2O, crystallizes as a purple crystal. This species adopts a distorted square-pyramidal geometry in which the TMC ligand assumes the trans-I configuration and the chloride ion binds in the syn-methyl pocket of the ligand. The Co^(II) ion adopts an S = 3/2 spin state, as measured by the Evans NMR method, and UV–visible spectroscopic studies indicate that the title hydrated salt is stable in solution. Density functional theory (DFT) studies reveal that the geometric parameters of [Co^(II)Cl(TMC)]Cl·2H_2O are sensitive to the cobalt spin state and correctly predict a change in spin state upon a minor perturbation to the ligand environment

Occlusion-Aware Crowd Navigation Using People as Sensors

Autonomous navigation in crowded spaces poses a challenge for mobile robots due to the highly dynamic, partially observable environment. Occlusions are highly prevalent in such settings due to a limited sensor field of view and obstructing human agents. Previous work has shown that observed interactive behaviors of human agents can be used to estimate potential obstacles despite occlusions. We propose integrating such social inference techniques into the planning pipeline. We use a variational autoencoder with a specially designed loss function to learn representations that are meaningful for occlusion inference. This work adopts a deep reinforcement learning approach to incorporate the learned representation for occlusion-aware planning. In simulation, our occlusion-aware policy achieves comparable collision avoidance performance to fully observable navigation by estimating agents in occluded spaces. We demonstrate successful policy transfer from simulation to the real-world Turtlebot 2i. To the best of our knowledge, this work is the first to use social occlusion inference for crowd navigation.Comment: 7 pages, 4 figure

Association of Prenatal Urinary Concentrations of Phthalates and Bisphenol A and Pubertal Timing in Boys and Girls.

BackgroundAnimal studies suggest that phthalates and bisphenol A (BPA), endocrine-disrupting chemicals found in many consumer products, may impact the timing of puberty.ObjectivesWe aimed to determine the association of prenatal exposure to high-molecular-weight phthalates and BPA with pubertal timing in boys and girls participating in the Center for the Health Assessment of Mothers and Children of Salinas (CHAMACOS) longitudinal cohort study.MethodsWe quantified urinary concentrations of eight phthalate metabolites and BPA at two time points during pregnancy among participating mothers ([Formula: see text]) and conducted clinical Tanner staging of puberty on their children every 9 months between 9 and 13 y of age. We conducted accelerated failure time models and examined the role of child overweight/obese status in this association.ResultsThe sum of urinary metabolites of di(2-ethylhexyl) phthalate [Formula: see text], monobenzyl phthalate (MBzP), and BPA were associated with later onset of at least one of the three outcomes assessed in girls (thelarche, pubarche, or menarche) and with earlier onset of at least one of the two outcomes assessed in boys (gondarche and pubarche). We found that monocarboxynonyl phthalate, monocarboxyoctyl phthalate, mono(3-carboxypropyl) phthalate, and BPA were associated with later pubarche and menarche mostly among normal-weight girls but not overweight/obese girls. MBzP was associated with later thelarche in all girls, and [Formula: see text] was associated with later thelarche and menarche in all girls. BPA and all phthalate biomarkers were associated with earlier gonadarche and pubarche in all boys as well as in overweight/obese boys when stratified by weight. Among normal-weight boys, associations with BPA were also inverse, whereas associations with phthalate metabolites were close to the null or positive.ConclusionsSeveral high-molecular-weight phthalates and BPA were associated with later puberty in girls and earlier puberty in boys included in the CHAMACOS cohort study. Childhood overweight/obesity may modify these associations. https://doi.org/10.1289/EHP3424

The End of History? Using a Proof Assistant to Replace Language Design with Library Design

Functionality of software systems has exploded in part because of advances in programming-language support for packaging reusable functionality as libraries. Developers benefit from the uniformity that comes of exposing many interfaces in the same language, as opposed to stringing together hodgepodges of command-line tools. Domain-specific languages may be viewed as an evolution of the power of reusable interfaces, when those interfaces become so flexible as to deserve to be called programming languages. However, common approaches to domain-specific languages give up many of the hard-won advantages of library-building in a rich common language, and even the traditional approach poses significant challenges in learning new APIs. We suggest that instead of continuing to develop new domain-specific languages, our community should embrace library-based ecosystems within very expressive languages that mix programming and theorem proving. Our prototype framework Fiat, a library for the Coq proof assistant, turns languages into easily comprehensible libraries via the key idea of modularizing functionality and performance away from each other, the former via macros that desugar into higher-order logic and the latter via optimization scripts that derive efficient code from logical programs

Unravelling the spatial variation of nitrous oxide emissions from a step-feed plug-flow full scale wastewater treatment plant

This work is licensed under a Creative Commons Attribution 4.0 International License. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in the credit line; if the material is not included under the Creative Commons license, users will need to obtain permission from the license holder to reproduce the material. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/Plug-flow activated sludge reactors (ASR) that are step-feed with wastewater are widely adopted in wastewater treatment plants (WWTPs) due to their ability to maximise the use of the organic carbon in wastewater for denitrification. Nitrous oxide (N2O) emissions are expected to vary along these reactors due to pronounced spatial variations in both biomass and substrate concentrations. However, to date, no detailed studies have characterised the impact of the step-feed configuration on emission variability. Here we report on the results from a comprehensive online N2O monitoring campaign, which used multiple gas collection hoods to simultaneously measure emission along the length of a full-scale, stepfed, plug-flow ASR in Australia. The measured N2O fluxes exhibited strong spatial-temporal variation along the reactor path. The step-feed configuration had a substantial influence on the N2O emissions, where the N2O emission factors in sections following the first and second step feed were 0.68% ± 0.09% and 3.5% ± 0.49% of the nitrogen load applied to each section. The relatively high biomass-specific nitrogen loading rate in the second section of the reactor was most likely cause of the high emissions from this section

Learning Task Skills and Goals Simultaneously from Physical Interaction

In real-world human-robot systems, it is essential for a robot to comprehend human objectives and respond accordingly while performing an extended series of motor actions. Although human objective alignment has recently emerged as a promising paradigm in the realm of physical human-robot interaction, its application is typically confined to generating simple motions due to inherent theoretical limitations. In this work, our goal is to develop a general formulation to learn manipulation functional modules and long-term task goals simultaneously from physical human-robot interaction. We show the feasibility of our framework in enabling robots to align their behaviors with the long-term task objectives inferred from human interactions.Comment: 2 pages, 1 figure. Accepted by CASE 2023 Special Session on The Next-Generation Resilient Cyber-Physical Manufacturing Network

Towards Robots that Influence Humans over Long-Term Interaction

When humans interact with robots influence is inevitable. Consider an autonomous car driving near a human: the speed and steering of the autonomous car will affect how the human drives. Prior works have developed frameworks that enable robots to influence humans towards desired behaviors. But while these approaches are effective in the short-term (i.e., the first few human-robot interactions), here we explore long-term influence (i.e., repeated interactions between the same human and robot). Our central insight is that humans are dynamic: people adapt to robots, and behaviors which are influential now may fall short once the human learns to anticipate the robot's actions. With this insight, we experimentally demonstrate that a prevalent game-theoretic formalism for generating influential robot behaviors becomes less effective over repeated interactions. Next, we propose three modifications to Stackelberg games that make the robot's policy both influential and unpredictable. We finally test these modifications across simulations and user studies: our results suggest that robots which purposely make their actions harder to anticipate are better able to maintain influence over long-term interaction. See videos here: https://youtu.be/ydO83cgjZ2

Assessing distributed leadership for learning and teaching quality: a multi-institutional study

Distributed leadership has been explored internationally as a leadership model that will promote and advance excellence in learning and teaching in higher education. This paper presents an assessment of how effectively distributed leadership was enabled at five Australian institutions implementing a collaborative teaching quality development scheme called the Peer Assisted Teaching Scheme. The Scheme brings together expertise from teams of academics, coordinators, and institutional learning and teaching portfolio holders to the shared goal of enhancing learning and teaching quality. A distributed leadership benchmarking tool was used to assess the Scheme’s effectiveness, and we found that (i) the Scheme is highly consistent with the distributed leadership benchmarks, and that (ii) the benchmarking tool is easily used in assessing the alignment (or otherwise) of teaching and learning quality initiatives with distributed leadership benchmarks. This paper will be of interest to those seeking to assess implementations of distributed leadership to improve teaching quality and leadership capacity

Effects of ACTH, dexamethasone, and adrenalectomy on 11β-hydroxylase (CYP11B1) and aldosterone synthase (CYP11B2) gene expression in the rat central nervous system

Using a highly sensitive quantitative RT-PCR method for the measurement of CYP11B1 (11β-hydroxylase) and CYP11B2 (aldosterone synthase) mRNAs, we previously demonstrated that CYP11B2 expression in the central nervous system (CNS) is subject to regulation by dietary sodium. We have now quantified the expression of these genes in the CNS of male Wistar Kyoto (WKY) rats in response to systemic ACTH infusion, dexamethasone infusion, and to adrenalectomy. CYP11B1 and CYP11B2 mRNA levels were measured in total RNA isolated from the adrenal gland and discrete brain regions using real-time quantitative RT-PCR. ACTH infusion (40 ng/day for 7 days, N=8) significantly increased CYP11B1 mRNA in the adrenal gland, hypothalamus, and cerebral cortex compared with animals infused with vehicle only. ACTH infusion decreased adrenal CYP11B2 expression but increased expression in all of the CNS regions except the cortex. Dexamethasone (10 μg/day for 7 days, N=8) reduced adrenal CYP11B1 mRNA compared with control animals but had no significant effect on either gene's expression in the CNS. Adrenalectomy (N=6 per group) significantly increased CYP11B1 expression in the hippocampus and hypothalamus and raised CYP11B2 expression in the cerebellum relative to sham-operated animals. This study confirms the transcription of CYP11B1 and CYP11B2 throughout the CNS and demonstrates that gene transcription is subject to differential regulation by ACTH and circulating corticosteroid levels