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Professional STEM societies have been identified as an important lever to address STEM diversity, equity, and inclusion. In this "Perspectives" article, we chronicle the highlights of the first Amplifying the Alliance to Catalyze Change for Equity in STEM Success (ACCESS+) convening held in September 2021. Here, we introduce the three-part ACCESS+ approach using a model that entails (i) completion of a DEI self-assessment known as the equity environmental scanning tool, (ii) guided action plan development and iteration, and (iii) sustained participation in a community of practice.

During associative retrieval, the brain reinstates neural representations that were present during encoding. The human medial temporal lobe (MTL), with its subregions hippocampus (HC), perirhinal cortex (PRC), and parahippocampal cortex (PHC), plays a central role in neural reinstatement. Previous studies have given compelling evidence for reinstatement in the MTL during explicitly instructed associative retrieval. High-confident recognition may be similarly accompanied by recollection of associated information from the encoding context. It is unclear, however, whether high-confident recognition memory elicits reinstatement in the MTL even in the absence of an explicit instruction to retrieve associated information. Here, we addressed this open question using high-resolution fMRI. Twenty-eight male and female human volunteers engaged in a recognition memory task for words that they had previously encoded together with faces and scenes. Using complementary univariate and multivariate approaches, we show that MTL subregions including the PRC, PHC, and HC differentially reinstate category-sensitive representations during high-confident word recognition, even though no explicit instruction to retrieve the associated category was given. This constitutes novel evidence that high-confident recognition memory is accompanied by incidental reinstatement of associated category information in MTL subregions, and supports a functional model of the MTL that emphasizes content-sensitive representations during both encoding and retrieval.

High‐speed underwater wireless optical communication holds immense promise in ocean monitoring and surveys, providing crucial support for the real‐time sharing of observational data collected by autonomous underwater vehicles (AUVs). However, due to inaccurate target information and external interference in unknown environments, link alignment is challenging and needs to be addressed. In response to these challenges, we propose a reinforcement learning‐based alignment method to control the AUV to establish an optical link and maintain alignment. Our alignment control system utilizes a combination of sensors, including a depth sensor, Doppler velocity log (DVL), gyroscope, ultra‐short baseline device, and acoustic modem. These sensors are used in conjunction with a particle filter to observe the environment and estimate the AUV's state accurately. The soft actor‐critic algorithm is used to train a reinforcement learning‐based controller in a simulated environment to reduce pointing errors and energy consumption in alignment. After experimental validation in simulation, we deployed the controller on an actual AUV called Tri‐TON. In experiments at sea, Tri‐TON maintained the link and angular pointing errors within 1 m and 10∘ $1{0}^{\circ }$, respectively. Experimental results demonstrate that the proposed alignment control method can establish underwater optical communication between AUV fleets, thus improving the efficiency of marine surveys. [ABSTRACT FROM AUTHOR]

This research explores the SL-Block system within an architecture framework by embracing building modularity, combinatorial design, topological interlocking, machine learning, and tactile sensor-based robotic assembly. The SL-Block, composed of S and L-shaped tetracubes, possesses a unique self-interlocking feature that allows for reversible joining and the creation of various 2D or 3D structures. In architecture modularity, the high degree of reconfigurability and adaptability of the SL-Block system introduces a new element of interest. Unlike modularization strategies that emphasize large-scale volumetric modules or standardized building components, using small-scale generic building blocks provides greater flexibility in maximizing design variations and reusability. Furthermore, the serial repetition and limited connectivity of building elements reduce the efforts required for bespoke manufacturing and automated assembly. In this article, we present our digital design and robotic assembly strategies for developing dry-jointed modular construction with SL-Blocks. Drawing on combinatorics and graph theory, we propose computational design methods that can automatically generate hierarchical SL-Block assemblies from given shapes. To address the physical complexities of contact-rich assembly tasks, we develop robotics using two distinct methods: pre-programmed assembly and sensor-based reinforcement learning. Through a series of demonstrators, we showcase the ability of SL-Blocks not only to reconfigure conventional building tectonics but also to create new building configurations. [ABSTRACT FROM AUTHOR]

Mobile monitoring is used as an additional tool to collect air quality data at a high spatial resolution and to complement data from fixed air quality stations. Citizens are interested in contributing to air quality monitoring, and while the availability of low-cost air quality sensors can create opportunities to measure the air quality at a high spatial resolution, the data are often of lower quality, and sensors that measure combustion-related aerosols (like black carbon) are not commonly available. Mobile monitoring using a mid-range instrument can fill this gap. We present the results of a mobile BC (black carbon) monitoring campaign performed by citizens in Mechelen as part of a local citizen observatory (CO), Meet Mee Mechelen, initiated as part of the European H2020 project, Ground Truth 2.0. The goal of the study was two-fold: (1) to propose and evaluate a mobile monitoring method (data collection and data processing) to construct pollution maps of BC concentrations and (2) to demonstrate how to organize community-based air quality monitoring to measure both the spatial and temporal variations in air pollution levels. Measurements were taken during peak hours in four campaigns characterized by different meteorological conditions: October–November 2017, February–March 2018, June–July 2018 and September 2018. The results show large spatial and temporal variabilities. Spatial variability is influenced by traffic volume, stop-and-go traffic and also the building environment and the distance of biking paths from road traffic. The four different campaigns show similar spatial patterns, but due to background and meteorological influences, the absolute concentrations differ between seasons. A rescaling method using data from fixed stations in the air quality monitoring network (AQMN) was presented to construct maps representative of longer periods. This paper shows that mobile measurements can be used by CO to assess the spatial variability of air quality in a city. The data can be used to evaluate mobility plans, carry out hot spot detection, evaluate the exposure of cyclists as a function of cycling infrastructure and perform model validation. However, it is important to use high-quality instruments and apply the correct measurement methodology (number of repetitions, season) to obtain meaningful data. [ABSTRACT FROM AUTHOR]

Child Sexual Abuse (CSA) and the production, use, and distribution of Child Sexual Abuse Material (CSAM) are key threats to children's mental health. From the perspective of indicated prevention, it can be assumed that some persons with a sexual interest in children commit such unreported crimes. Accordingly, the German Network kein Täter werden (meaning do not offend) has implemented a confidential treatment service for persons with a sexual interest in minors who voluntarily seek therapy, might or might not have offended but have not yet been detected or have fulfilled all legal requirements (here referred to as non-forensic individuals). However, this offer has been questioned for investing resources in a group which critics consider as low risk. The following study addresses the question of recidivism risks for CSA or viewing CSAM among non-forensic individuals. We found significantly higher rates of CSA/CSAM in our participants' history compared to a German study on a representative sample of males. Regarding CSAM, the recidivism rate of 39% was found to be 11 times higher than the expected recidivism rate based on previous publications. Regarding CSA, the recidivism rate of 14% was not significantly different from the expected rate reported for subjects with a conviction for a sexual contact offense. Among various risk instruments, only the CPORT with CASIC rating was able to predict CSA (AUC = 0.69, 95% CI = 0.55, 0.82) and CSAM (AUC = 0.63, 95% CI = 0.53, 0.73) among individuals with a history of CSAM, but with poor discrimination. We conclude that a large proportion of our sample poses a substantial risk and therefore treatment resources are well invested. However, further studies are needed to improve risk assessment among non-forensic clients. [ABSTRACT FROM AUTHOR]

Over the past decade, firms' recruitment problems have increased significantly in Germany. We show that skill shortages have been more pronounced in rural areas and that the gap between rural and urban regions has slightly increased. The intensity of a local skill shortage is linked to regional labour market conditions, the occupational composition and the share of small establishments. However, the most important factor is a more advanced demographic change in rural areas. Of all factors considered, the proportion of older workers correlates most strongly with the regional vacancy rate. [ABSTRACT FROM AUTHOR]

Ziel des Beitrags ist die Untersuchung und Bewertung der Erreichbarkeit der Bevölkerung durch ambulante Pflegedienste in Unterfranken unter Einbeziehung der räumlich differenzierten Bevölkerungsstruktur für das Jahr 2017 sowie der voraussichtlichen demographischen Entwicklung bis 2025. Die Erreichbarkeiten werden sowohl rasterbasiert als auch vektorbasiert in einer GIS-Software modelliert. Darüber hinaus werden demographische Entwicklungen in der Altersgruppe „80 Jahre und älter“ eingebunden. Die Ergebnisse der rasterbasierten Fahrzeitenmodellierung zeigen flächenhaft relativ gute Erreichbarkeiten, mit Ausnahme weniger peripherer Gebiete. Mittels vektorbasierter Fahrzeitenmodellierung werden Einzugsgebiete, welche auf Personalkosten und Anfahrtspauschalen nach SGB V und SGB XI als Berechnungsgrundlagen basieren, für ambulante Pflegedienste berechnet. Es zeigt sich, dass in Teilen Unterfrankens keine ausreichende Kostendeckung gegeben ist. Hinsichtlich der skizzierten Bevölkerungsentwicklung sowie unzureichender Fahrtkostendeckung im Bereich der Mittelgebirge und abseits der Verdichtungsräume wird eine Flexibilisierung der Anfahrtsvergütung sowie eine Aufstockung des Pflegepersonals empfohlen.