Ford (Germany)

Combined sewer overflows (CSO) are a significant source of urban water pollution, with sediments originating from sewers contributing substantial loads of organic matter, nutrients, and particulate-associated contaminants to receiving waters. In Germany, constructed wetlands for CSO treatment (CSOCWs) are well-established, yet their large surface area limits their implementation in urban areas. The present study investigates the potential of compact CSOCWs, operated at doubled flow rate, with tailored filter substrates and the addition of biopolymers to enhance treatment performance. A series of flocculation experiments was first conducted to identify a suitable biopolymer for CSO treatment. Subsequently, small-scale pilot column tests were performed to evaluate compact CSOCW configurations. Here, different filter substrates were investigated, including sand, sand-gravel, gravel, shells, sand-activated carbon, and sand-zeolite, with and without the selected biopolymer introduced into the inflow to assess its effect on treatment performance. Results show that compact CSOCWs with suitable substrates and increased flow rates achieved removal efficiencies comparable to the reference CSOCW in standard operation, exhibiting only minor deviations. Sorptive and fine-grained substrates (activated carbon, zeolite) demonstrated high performance for particulates, COD, DOC, and NH4N, respectively. Biopolymer dosing significantly enhanced particle and COD retention in coarse filter substrates (gravel, shells), thereby reducing performance differences across configurations. In contrast, phosphorus removal remained limited across all configurations, independent of biopolymer dosing. These findings demonstrate that compact CSOCWs can provide a robust treatment option for CSOs and urban runoff under increased hydraulic loading, particularly in densely populated areas.

In technology-enhanced education, there is always a mutual impact between pedagogy and technology. To maximize educational effectiveness while leveraging the appeal of contemporary technology, educators and developers have introduced time travel exploratory games. To meet the needs of occupational accident prevention—a task of societal relevance for the protection of human health and life, the avoidance of damage and major financial losses, and for the protection of the environment—these exploratory games have been enhanced into time travel prevention games. The phenomenon of time travel allows for, and even fosters, a deeper dovetailing of pedagogy and technology. During accident prevention training, participants who have caused a—fortunately, only virtual—disaster are offered the option of time travel. By returning to an earlier stage of the training, they have the opportunity to change the outcome and to achieve better results on their next attempt. This approach relies on insights into the role of human mental time travel in episodic knowledge representation. From a pedagogical perspective, educational game design means the anticipation and preparation of stories of success to be experienced during game-based training. Essential elements of these stories should be memorable and even worth retelling. From a technological perspective, a trainee’s mental time travel is digitally implemented—technology makes daydreams come true. Within practical training modules, several original and innovative concepts have been developed, implemented, and applied, such as modifications of the past that make pedagogical concepts operational.

Sport tourism, business events, festivals, and mass gatherings draw crowds that contribute to tourism and community development. However, extreme weather is disrupting events globally, exposing organisers and host destinations to risk as climate changes. This research analyses events affected by extreme weather in terms of location, purpose, and format using a global sample of 2,091 events reported as disrupted from 2004-2024. Qualitative insights are shared about the size, financial effects, and complexity of encounters, along with connections to extreme weather attribution research. While limited data prevents firm conclusions about global incidents, patterns related to crowds and trends over time in mature, English-speaking event economies (the US, UK, Canada, and Australia) are discussed, including the apparent increase in incidents across these countries. Overall, storms and their effects are found to be the most disruptive type of weather, however, there is regional variation. Arts, culture and entertainment events, particularly festivals and concerts, bear the brunt of impacts, followed by social and sporting events, although the picture varies among the four countries analysed. Findings help event organisers, destinations, and emergency managers better understand the specific weather risks that impact the timing, location, format, and viability of events, providing insights that can improve adaptation and resilience.

In this paper, we present a pallet detection system utilizing the You only look once X (YOLOX) machine learning method to identify two different types of pallets in various environments. The sensor technology employed in this system is capable of capturing both RGB and depth images, providing a comprehensive view of the environment. YOLOX, an advanced object detection algorithm, is used to enhance the accuracy and efficiency of pallet recognition. Despite the challenges posed by a relatively small dataset available for training, our system demonstrates robust performance in both offline simulations and live operational environments. The presence of two different types of pallets further adds complexity to the classification process, highlighting the effectiveness of YOLOX in handling diverse scenarios.

Tujuan penelitian ini adalah untuk mendeskripsikan peningkatan hasil belajar dengan model problem based learning berbantuan media baju energi terhadap kemampuan menulis peserta didik kelas IV SD 3 Wergu Wetan pada mata pelajaran IPAS materi energi. Penelitian ini menggunakan penelitian tindakan kelas (PTK). Subjek dari penelitian ini adalah seluruh siswa kelas VI SD 3 Wergu Wetan yang berjumlah 26 peserta didik. Metode pengumpulan data yang digunakan yaitu tes, dokumentasi, dan observasi. Hasil penelitian di atas setelah dilakukan penerapan model problem based learning berbantuan media baju energi terhadap hasil belajar diperoleh peningakatan. Siklus 1 diperoleh rata-rata hasil belajar peserta didik sebesar 77,27. Peserta didik yang tuntas sebanyak 17 dengan persentase 65,38% dan peserta didik yang tidak tuntas sebanyak 9 dengan persentase 34,62%. Pada siklus 2 hasil belajar meningkat dengan perolehan rata-rata peserta didik sebesar 84. Peserta didik yang tuntas sebanyak 25 siswa dengan persetase 96,15% dan 1 siswa tidak tuntas dengan persentase 3,85%.

Human-wildlife conflicts are generally tackled using single-species studies and ensuing management solutions, ignoring species interactions that may moderate or augment these issues. We investigate the effects of interactions between four goose species foraging in the province of Friesland, the Netherlands, on species distributions, energetics, and consequent economic costs of agricultural damages and management, using an individual-based model. In Friesland, geese are allowed to graze on (semi-)natural grasslands and selected agricultural grasslands (accommodation areas), while they are scared off other agricultural grasslands (scaring areas). We show that interspecific competition and facilitation drive spatial redistribution of goose species. With increasing population sizes, most species are forced to increase foraging in the scaring areas, leading to more scaring events and more additional foraging to compensate for energy spent on fleeing behaviour. Our modelling results underline that careful consideration should be given to how management may affect the spatial distribution of foraging geese.Supplementary InformationThe online version contains supplementary material available at 10.1007/s13280-025-02206-9.

Abstract Fluktuierende Materialeigenschaften sind Ursache für Fertigungsfehler und Ausschuss bei produzierenden Unternehmen. Die derzeit üblichen Methoden der Materialcharakterisierung sind zeitaufwändig und kostspielig und erlauben es den Produzenten, trotz dessen nicht ihre Fertigungsprozesse präzise und dynamisch auf Änderungen im Materialverhalten zu adjustieren. Das „digitale Coil“ bezeichnet einen Ansatz, der darauf abzielt durch den Einsatz vollumfänglicher Charakterisierungsmethoden in Kombination mit den fortgeschrittenen Möglichkeiten zur Datenauswertung von heute Transparenz in die „Black-Box“ Material zu bringen, um so wissensbasierte Entscheidungen bei der Prozessparametrierung zu ermöglichen.

<div class="section abstract"><div class="htmlview paragraph">The use of drum brakes in Battery Electric Vehicles (BEVs) offers numerous benefits, including energy efficiency, reduced brake dust emissions, and reliable performance under challenging weather conditions. The capability of regenerative braking reduces the friction brake application frequency in BEVs and therefore the brakes can be prone to corrosion and performance degradation especially considering conventional disc brake systems. The closed design of a drum brake prevents corrosion of the friction-components by sealing out water, dirt or snow. A common sealing concept is performed with a labyrinth between the gap of the rotating drum and the axle mounted backplate. A hermetical isolation of water and snow ingress into the drum cannot be achieved with this concept, so additional aerodynamic measures are necessary to deflect the air/water path and protect the inner brake components. Additionally, interfaces like wheel cylinders, electric park brake parts, brake shoe pins, and axle mountings can potentially lead to leaks on the backplate. This study highlights the impact of water/snow ingress on the example of a frozen parking brake during cold climate on-road testing. Through scientific investigation using the state-of-the-art fluorescence method, drum leakages were visualized, and the extent of water ingress was measured. Multiple multiphase CFD simulations supported the design phase of the aerodynamic measures. Subsequently, the vehicle was cooled down to -10 °C to simulate the cold climate test conditions. The frozen parking brake situation could be reproduced with this method, and beneficial aerodynamic and sealing measures were extrapolated to avoid the drum brake from freezing. The tests were conducted in the FKFS Thermal Wind Tunnel, a wind tunnel comprising a two-axle-dynamometer and water irrigation systems with UV illumination.</div></div>

Abstract Migratory species experience various conditions and events throughout their annual cycle that influence their spatial and demographic dynamics. To understand these dynamics, it is essential to describe the origin and destination of individuals. Migratory connectivity, which is defined as the geographic linkage between populations across the annual cycle, is increasingly incorporated in population models to relate population trends to environmental variables at different stages of the cycle. However, such information on migratory movements is obtained independently from the study of population dynamics despite the interaction between both processes. Expanding on the growing use of integrated modelling approaches, we developed an integrated framework that allows the sharing of information between migratory connectivity and population data. We first assembled an integrated migratory connectivity model and an integrated population model to join the analysis of GPS, live‐reencounter, dead‐recovery, capture–mark–recapture, and population count data within a unified framework. Based on simulated data, we assessed the ability of the resulting integrated connectivity and population model to produce unbiased and precise connectivity and demographic estimates. We then applied the same assessment to real data using the Eurasian Curlew (Numenius arquata) as a case study. On simulated data, the integrated connectivity and population model estimated connectivity and survival parameters with no bias and similar precision to the connectivity model alone. However, it outperformed the population model in estimating fecundity in the absence of explicit productivity data. When applied to the Eurasian Curlew, the integrated connectivity and population model produced overall similar migratory connectivity and more accurate demographic estimates than the connectivity model alone, consistent with previous studies. Additionally, the model was able to estimate fecundity, whereas the data were too sparse for the population model alone to disentangle juvenile survival and fecundity. The sharing of information between migratory connectivity and population data improved the estimation of demographic parameters by the population model and improved connectivity parameter estimates when data were scarce. This flexible framework can be generalised to include diverse data on migration movements, population structure, individual heterogeneity or environmental variables, allowing further investigation of the interaction between migration patterns and population dynamics.