Prognose der Verkehrslage in der Region Hannover

Die primäre Anforderung der Verkehrsteilnehmer im Bereich des Straßenverkehrs ist die Kenntnis der aktuellen Verkehrslage. Diese basiert in der Regel auf der wirklich benötigten Reisezeit von sehr vielen Verkehrsteilnehmern, deren Daten häufig im Kontext von Routingdiensten abgegriffen werden.

Im Rahmen von Data4UrbanMobility wurden Werkzeuge entwickelt um eine ganglineinbasierte Prognose der Verkehrslage zu ermöglichen. Die folgende Abbildung zeigt eine Oberfläche auf der typische Ganglinienverläufe und Ausreißer visualisiert werden.

Die Prognose der Verkehrslage kann dann mittels einer Karte für den Endnutzer visualisert werden:

Erste Version der MIC-App bereitgestellt

Eine erste Version der MIC-App (Move in the City) konnte allen Partnerinnen und Partnern des Projekts und einer geschützten Nutzer*innengruppe der Öffentlichkeit zur Verfügung gestellt werden. Die mobile App MiC ist ein Instrument zur Datenerhebung.

Dabei verknüpft MiC – eine Entwicklung des Institute for Sustainable Urbanism ISU der TU Braunschweig und Projektionisten GmbH Hannover – das wachsende Bewusstsein und die Notwendigkeit für digitale Bürger*innenrechte mit den Potentialen mittels der Auswertung großer Datenmengen neue Formen der menschzentrierten Entwicklung von Stadt und Mobilität zu ermöglichen stellt eine Möglichkeit dar, sich aktiv als Bürgerwissenschaftlerin und Bürgerwissenschaftler an der Forschung und Entwicklung der Mobilität für alle in der Stadt der Zukunft zu beteiligen.

MiC erhebt – durch die Nutzerinnen und Nutzer gesteuert – Daten zu Strecken und Art der Fortbewegung. Diese Daten werden pseudonymisiert, so dass ein Rückschluss auf die jeweilige Person nicht mehr möglich ist. Wichtig ist die Vielzahl der Nutzerinnen und Nutzer – nicht die einzelne Bewegung. Die Stadt der Zukunft zeichnet sich aus durch den barrierearmen Zugang zu Mobilität und Erreichbarkeit für alle. Der holistische Ansatz der Forscherinnen und Forscher des Institute for Sustainable Urbanism ISU (TU Braunschweig) sowie der Projektbeteiligten betrachtet Stadt dabei auf verschiedenen Maßstabsebenen und bringt intelligente Planungen – wie z.B. die 5-Minuten Stadt –, Städtebau und innovative Technologien zusammen. Für ein umfassendes Verständnis individueller Mobilität und darauf aufbauende neue Methoden und Werkzeuge für integrierte Verkehrs- und Stadtplanung werden mittels der MiC-App uns umfangreiche und detaillierte Daten darüber geliefert, wie und auf welchem Wege wir uns in der Stadt fortbewegen.

Entwicklungsstand:

In der ersten Version ermöglicht das Stadtforschungstool MiC den Nutzer*innen durch eine einfach Handhabung das Starten und Beenden der „Tracking-Time“ (Bild 1). Wichtig ist, die Nutzer*innen entscheidet selber über den Zeitraum. Als erstes Ergebnis für die Nutzer*innen steht eine Zusammenfassung ihrer bisher aufgezeichneten Routen (Bild2). In den Einstellung (Bild 3) kann der Nutzer sich aktiv an Feedback beteiligen (Bild 4) sowie seinen Account und somit seiner zur Verfügung gestellten Daten löschen (Bild 5).

von links nach recht: Bild1-5 MIC App Interface – Attribution-NonCommercial-ShareAlike 4.0 International  (CC BY-NC-SA 4.0)

Die aktuelle Weiterentwicklung sieht eine Visualisierung der Routen für den jeweiligen Nutzer vor.

Um Teil der Testgruppe zu werden ist zur Zeit noch eine Anmeldung unter: www.mic-app.org notwendig. Die Anwendung ist nicht frei im App Store / GooglePlay Store zu erhalten.

Auf der Internetseite www.mic-app.org wird zusätzlich detailliert auf häufige Fragen (FAQ) zur Anwendung sowie über Entwicklungen und Neuheiten informiert

D4UM Plattform und Dashboard V2

Die neue Version der Plattform inklusive des Dashboards gibt noch detailliertere Auskünfte über die Verkehrssituation

Die farblich unterschiedlichen Label lassen eine schnelle Unterscheidung zwischen den verschiedenen Event typen zu. Durch das klicken auf eines der Events wird der typically affected subgraph angezeigt für diesen Eventtyp.

Beispiele: Visualisierungen eines Konzerts und eines Fußballspiels

Zusätzlich gibt der Graph in der oberen rechten Ecke Auskunft über die Verkehrssituation vor und nach dem Eventstart.

{API}
Es wurden die API Endpunkte mit zusätzlichen Information erweitert.
Diese werden mittels der als Teil der Forschung entwickelten Modellen erstellt.

Erste Version der D4UM-App bereitgestellt

Eine erste Version der D4UM-App konnte allen Partnern des Projekts zur Verfügung gestellt werden. Die App stellt eine Möglichkeit dar, sich Fahrtauskünfte mit dem öffentlichen Personennahverkehr in Niedersachsen und Bremen (Datengrundlage: EFA – elektronische Fahrplanauskunft für Niedersachsen und Bremen) ausgeben zu lassen. Im Fokus stand hierbei, dass der Nutzer schnell und einfach an die für ihn wichtigen Informationen gelangen kann, um so seine Reise möglichst simpel planen zu können.

Folgende Funktionen dienen dabei in der ersten Version der schnellen Auskunft:

Abfahrten und Verbindungen

Über die Funktion Abfahrten lassen sich Abfahrtszeiten an einer bestimmten oder an nahegelegenen Haltestellen ermitteln. Unter Verbindungen können hingegen Fahrtvorschläge von einem Startpunkt (Adresse oder Haltestelle) zu einem Zielpunkt gesucht werden. Zeiten stehen dabei auch in Echtzeit zur Verfügung, sodass auch Verspätungen direkt von dem Nutzer erkannt werden können.

Karte

Über die Karte sind alle Haltestellen zu finden, sodass sich der Nutzer einen Überblick über die nähere Umgebung oder auch den Weg zur Haltestelle oder einem Ziel verschaffen kann.

Wird auf der Karte auf ein Haltestellensymbol oder den zugehörigen Haltestellennamen geklickt, öffnet sich der Abfahrtsmonitor zu dieser Haltestelle. Die nächsten Abfahrten können somit auch über diesen Weg aufgerufen werden.

Darüber hinaus kann sich der Nutzer auch den Verlauf seiner Fahrt anzeigen lassen.

Menü/Einstellungen

Weitere Funktionen und Einstellungen finden sich ergänzend im Menü der App.

Der Nutzer bekommt hier zum einen die Möglichkeit, dass erweiterte Einstellungen zu den Suchanfragen bei Verbindungen oder Abfahrten vorgenommen werden können, und zum anderen, dass er weitere Features verwenden kann. Darunter befindet sich zum Beispiel das Feedbackformular. Hierüber kann unkompliziert Kontakt mit den Entwicklern der D4UM-App per Mail aufgenommen werden. Icons ermöglichen es, dass ein Eindruck zu der App übermittelt werden kann. Ein weiteres Feld für Freitext bietet zudem Platz für individuelle Kritik und einer Meinung zu der App. So kann in Zukunft kundennah an der App weiterentwickelt und einfach auf Wünsche und Meinungen reagiert werden.

Quantifizierungen und Vorhersage von Auswirkungen von Veranstaltungen

Neue Data4UrbanMobility-Forschungsergebnisse ermöglichen es, die räumlichen Auswirkungen von Veranstaltungen zu quantifizieren und vorherzusagen. Dazu werden zusammenhängende, betroffene Straßenabschnitte in der Nähe von Veranstaltungen identifiziert. Auf dieser Grundlage kann dann die räumliche Auswirkung quantifiziert werden. Das Verfahren ist in der folgenden Grafik dargestellt.

(Karte von https://www.openstreetmap.org)

Hier in Gelb markiert ist eine Veranstaltung, in Rot betroffene Straßenabschnitte und in Dunkelblau die gemessene Auswirkung. Weiterhin wurden Verfahren des Maschinellen Lernens angewandt, um diese Auswirkungen zu prognostizieren. Dabei konnte der Fehler gegenüber bestehenden state-of-the-art Ansätzen um bis zu 40% verringert werden.

D4UM – Plattform V1 fertiggestellt

Die erste Version der Data4UrbanMobility Plattform wurde fertiggestellt. Dazu wurde zunächst eine 3-Schichten Architektur der Plattform konzipiert und implementiert. Die Plattform bietet RESTfull Webservices für Mobilitätsapplikationen wie Dashboard-Anwendungen oder Apps an. Als erste Beispielanwendung wurde dazu eine interaktive Karte entwickelt, die die Auswirkungen von Veranstaltungen visualisiert. Ein Ausschnitt aus der Anwendung ist im folgenden Screenshot zu sehen.

Zu sehen sind 4 Veranstaltungen in Hannover. Die Farben entsprechen dabei unterschiedlichen Veranstaltungsarten (etwa Konzerte, Messen, Fußballspiele). Die Kreise visualisieren die räumlichen Auswirkungen, die diese Veranstaltungen auf den Verkehr hatten.

Umfangreicher Anforderungskatalog
Die Data4UrbanMobility Anforderungsanalyse umfasst die Erfassung der Anforderungen der Anwendungspartner Region Hannover (RH) und Wolfsburg AG (WAG), sowie der nicht-funktionalen Anforderungen. Aus den Anforderungen der AnwendungspartnerInnen (RH und WAG), die von MOMA erhoben wurden, sind von L3S Forschungsfragen für die Datenanalyse abgeleitet worden, die sich speziell auf die Informationsbedürfnisse der AnwenderInnen beziehen und im weiteren Projektverlauf adressiert werden.

Die aktuelle Forschungsfragen adressieren insbesondere:

1.  Automatische Verifikation von Verkehrswarnmeldungen und Prognose von deren Auswirkungen.
2.  Identifikation von Veranstaltungen und Prognose verkehrsrelevanter Auswirkungen.
3. Korrelation von IV-Reiseflussdaten, EFA-Querylogs, Warnmeldungen und Twitterfeeds.
4. Bestimmung von optimalen Reisezeitpunkte.

Wachsende Datensammlung

Das ISU hat einen umfassende Datenmatrix mit potentiellen Quellen für mobilitätsrelevante Daten  erstellt. Das von L3S entwickelte Data4UrbanMobility Datenmodell beschreibt alle projektrelevanten Daten und setzt diese in Verbindung um die Daten sowohl für die Analyse als auch für die Anwendungen und Apps einheitlich zur Verfügung zu stellen. Die ausgewählten Datenquellen sind von L3S in das Data4UrbanMobility Datenmodell überführt. Einige der Datenquellen wie EFA-logs, und IV-Daten sind dabei auf deren Qualität geprüft worden.

Um die Datenintegration zu ermöglichen sind Werkzeuge zur Extraktion der relevanten Daten aus Mobilitätsrelevanten Datenquellen entwickelt worden:

• Straßen- und Graphextraktion aus OpenStreetMap
• EFA-Anfragen Bulkloader für die Extraktion der ÖPNV Anfragen aus EFA Logs
• Integration von Daten aus dem Zentralen Haltestellen Verzeichnis (ZHV) inklusive Verknüpfung der Daten mit den EFA-Anfragen

Die aktuelle Datensammlung (Stand: 12 Dezember 2017) umfasst:

EFA-Logs: 17 Mio. Suchanfragen
IV-Daten: 174 Tsd. Straßen, alle 15 Minuten
GTFS-Daten: 90 Tsd. Haltestellen, 2,6 Tsd. Routen
Wetter: Radolan Regenraster
Twitter: 2,5 Mio. Tweets ab Juni 2017

OSM: 440 Tsd. Straßen
Events: 21 Tsd. Veranstaltungen (14.08.2016-17.07.2018)

Warnmeldungen: 13 Tsd. Warnmeldungen (ab 06.2017)

Visualisierungen der ÖPNV Informationen

Zur intuitiven Analyse von mobilitätsrelevanten Informationen, insbesondere von ÖPNV Informationen, wurde von den PROJEKTIONISTEN (PROJ) eine Dashboard-Webapplikation konzipiert. Erste Prototypen visualisieren Anfragen an das regionale Fahrplanauskunftsystem EFA (www.efa.de) und dienen als Ausgangsbasis für explorative Analysen und die Implementierung der produktiven Version des Dashboards. Im Folgenden ist eine im Dashboard integrierte Visualisierung der häufigsten Start- und Ziel-punkte zu sehen.

Analysen der EFA-Logs
Als erste Forschungsfrage wird aktuell die Analyse der Auswirkungen der Veranstaltungen auf dem ÖPNV mit Methoden des Maschinellen Lernens analysiert.  Hierzu wurden in explorativen Datenanalysen der Einfluss von großen Veranstaltungen wie z.B. Fussballspielen und mittelgroßen Veranstaltungen, etwa Konzerte, auf Anfragen an den ÖPNV betrachtet.  Als Grundlage für umfassende Analysen wurden mit Hilfe visueller Methoden exemplarisch Korrelation zwischen ÖPNV-Nachfrage und Veranstaltungszeiträumen detektiert.

Dabei zeichnen sich z.B. für Hannovers Innenstadt klare, sternförmige Muster ab, die zentrale Mobilitätsknoten identifizieren.

Das Bild stellt die Luftlinie zwischen Start- und Ziel-Ort der Anfragen dar. Dabei entsprechen dunklere Farben häufigeren Strecken. Hier werden deutlich Hannover Hauptbahnhof und Hannover Kröpcke (die zentrale U-Bahn Station) als Mobilitätsknoten identifiziert.

Analysen der Nachfrage für einzelne Stationen lassen wochentagspezifische Muster erkennen.

Hier dargestellt sind die durchschnittliche Anzahl der Anfragen mit der Ziel-Haltestelle “Hannover Stadionbrücke”. Zu erkennen sind vor allem Unterschiede zwischen Werktagen und dem Wochenende.

Auch der Einfluss von Veranstaltungen kann mit Hilfe der Anfragen visualisiert werden:

Dargestellt sind die Anzahl der Anfragen mit Ziel “Hannover Stadionbrücke” für Mittwoch, den 26.04.2017 (Orange) sowie die durchschnittlichen Anzahl von Anfragen, die mittwochs mit gleichem Ziel gestellt wird (Blau).
An diesem Tag fand in einer nahe gelegenen Konzerthalle ein Konzert statt, das um 20 Uhr begann. Die signifikante Abweichung zwischen 17 und 19 Uhr wurde sehr wahrscheinlich von den anreisenden Gästen verursacht wurde. Dies illustriert, dass Anfragen an den ÖPNV eine wertvolle Informationsquelle sein können, um Prognosen über die Auswirkung von Veranstaltungen auf Mobilität zu erstellen.

• S4ConvD: Adaptive Scaling and Frequency Adjustment for Energy-Efficient Sensor Networks in Smart Buildings. Schaller, Melanie; Rosenhahn, Bodo (2025).
• Tunable superconductivity coexisting with the anomalous Hall effect in a transition metal dichalcogenide. Hossain, Md Shafayat; Zhang, Qi; Graf, David; Iraola, Mikel; Müller, Tobias; Mardanya, Sougata; Tu, Yi-Hsin; Lai, Zhuangchai; Soldini, Martina O.; Li, Siyuan; Yao, Yao; Jiang, Yu-Xiao; Cheng, Zi-Jia; Litskevich, Maksim; Casas, Brian; Cochran, Tyler A.; Yang, Xian P.; Kim, Byunghoon; Watanabe, Kenji; Taniguchi, Takashi; Chowdhury, Sugata; Bansil, Arun; Zhang, Hua; Chang, Tay-Rong; Fischer, Mark H.; Neupert, Titus; Balicas, Luis; Hasan, M. Zahid (2025). 16(1) 2399.

  Transition metal dichalcogenides display a high technological potential due to their wide range of electronic ground states. Here, we unveil that by tuning hydrostatic pressure P, a cascade of electronic phase transitions can be induced in the few-layer transition metal dichalcogenide 1T'-WS2. As P increases, we observe the suppression of superconductivity with the concomitant emergence of an anomalous Hall effect (AHE) at \\($\$\)Pbackslashapprox 1.15\\($\$\)GPa. Above 1.6GPa, we uncover a reentrant superconducting state emerging from a state still exhibiting AHE. This superconducting state competes with the AHE state and shows a marked increase in superconducting anisotropy with respect to the ambient pressure phase, suggesting a distinct pairing symmetry. We demonstrate that 1T'-WS2 concomitantly transitions into a strong topological phase with different band orbital characters and Fermi surfaces contributing to the superconductivity. These findings position 1T'-WS2 as a tunable superconductor, wherein superconductivity, AHE, and band features can be tuned reversibly.
• Exploring Design Choices for Autoregressive Deep Learning Climate Models. Gallusser, Florian; Hentschel, Simon; Krause, Anna; Hotho, Andreas (2025).
• A DEM differencing method for detecting geomorphic changes on topographically complex areas based on UAV remote sensing techniques. Li, Dou; Li, Pengfei; Hu, Jinfei; Yao, Wanqiang; Yan, Lu; Latifi, Hooman; Tang, Bingzhe; Liu, Lifeng (2025). 1–1.

  High-resolution topographic data acquired by unmanned aerial vehicles (UAV) have facilitated the use of digital elevation model (DEM) of difference (DoD) methods for studying geomorphic processes in complex terrain. However, insufficient understanding of systematic bias and random errors for DEMs constrained the application. In this study, we comprehensively analyzed the spatial pattern and magnitude of errors (including systematic and random errors) of DEMs derived from UAV-acquired point clouds for a topographically complex area (a sub-catchment of Qiaogou in the hilly and gully loess plateau (SC_QG), China). The relationships between random errors and influential factors associated with topography, point cloud density, vegetation and interpolation algorithms were also evaluated. On this basis, an error source thresholding (EST) method was adapted through incorporating residual systematic errors and including more impacting factors in the fuzzy inference system for random error estimation. The adapted EST method was then employed to quantify the DoD uncertainty and geomorphic changes in two small catchments with complex terrain (i.e. SC_QG and a sub-catchment of Telagou (SC_TLG) in the hilly and gully Loess Plateau, China), while the results were verified by the changes measured by Terrestrial laser scanning (TLS) and erosion pins, respectively. Results showed that mean value of systematic errors of DEMs were 0.065m and 0.005 m for SC_QG and SC_TLG, while the residual errors were reduced to 0.002 m and 0.001 m after co-registration, respectively. Significant statistical relationships (p<0.01) were found between random errors and influential factors. The erosional volume of two study sites detected by the adapted method were -252.29 m3 and -981.07m3 and the corresponding depositional volume were 30.57 m3 and 1594.32m3, respectively. The adapted method achieved a comparable pattern and magnitude of volumetric changes with TLS results, which was superior to the original EST method in SC_QG. Besides, our method showed a lower absolute error (0.034 m) compared to the original method (0.087 m) through a comparison with erosion pins measurement in the SC_TLG. Overall, the adapted EST method provided a reliable tool for geomorphic change detection in areas associated with complex terrain.
• Expression of Elongase- and Desaturase-Encoding Genes Shapes the Cuticular Hydrocarbon Profiles of Honey Bees. Rodríguez-León, Daniel Sebastián; Schmitt, Thomas; Pinto, María Alice; Thamm, Markus; Scheiner, Ricarda (2025). e17716.

  ABSTRACT Most terrestrial insects have a layer of cuticular hydrocarbons (CHCs) protecting them from desiccation and mediating chemical communication. The composition of these hydrocarbons is highly plastic and changes during their lifetime and with environmental conditions. How these changes in CHC composition are achieved is largely unknown. CHC profiles of Apis mellifera honey bees vary among castes, task groups and subspecies adapted to different climates. This makes A. mellifera an excellent model for studying the molecular mechanism underlying CHC biosynthesis. We correlated the expression of specific elongase- and desaturase-encoding genes with the CHC composition in bees performing different social tasks in two highly divergent A. mellifera subspecies. Elongases are enzymes that lengthen the hydrocarbon chain, while desaturases introduce double bonds in it. We evaluated the hypothesis that the expression of the genes encoding these enzymes determines CHC profiles of the worker bees. Our results revealed that the specificity of desaturases and elongases shapes the CHC profiles of worker bees performing different social tasks. Expression of the desaturase-encoding gene LOC100576797 and the elongase-encoding gene LOC550828 seemed to be strongly associated with the abundance of compounds that were characteristic of the CHC profile of nurse bees. In contrast, the compounds that characterised the CHC profiles of the forager bees seemed to be associated with the desaturase-encoding gene LOC551527 and the elongase-encoding gene LOC409638. Our data shed light on the genetic basis for task-specific CHC composition differences in social hymenopterans and paved the ground for unravelling the genetic underpinning of CHC biosynthesis.
• Finding all solutions of qKZ equations in characteristic \($p$\). Mukhin, Evgeny; Varchenko, Alexander (2025).
• The Installation Design of Solar Panels for Village Houses HK with Optimization-based Efficiency for Sustainable Environmental. Tsang, Tony; Chuen, Fong Lun; Mok, Gary; Poon, Steven; Lip, Samuel (2025).

  We use the kinematic data of the stars in eight dwarf spheroidal galaxies to assess whether \($f(R)$\) gravity can fit the observed profiles of the line-of-sight velocity dispersion of these systems without resorting to dark matter. Our model assumes that each galaxy is spherically symmetric and has a constant velocity anisotropy parameter \($\beta$\) and constant mass-to-light ratio consistent with stellar population synthesis models. We solve the spherical Jeans equation that includes the Yukawa-like gravitational potential appearing in the weak field limit of \($f(R)$\) gravity, and a Plummer density profile for the stellar distribution. The \($f(R)$\) velocity dispersion profiles depend on two parameters: the scale length \($\xi^-1$\), below which the Yukawa term is negligible, and the boost of the gravitational field \($\delta>-1$\). \($\delta$\) and \($\xi$\) are not universal parameters, but their variation within the same class of objects is expected to be limited. The \($f(R)$\) velocity dispersion profiles fit the data with a value \($\xi^-1= 1.2^+18.6_-0.9$\) Mpc for the entire galaxy sample. On the contrary, the values of \($\delta$\) show a bimodal distribution that picks at \($\bar\delta=-0.986\pm0.002$\) and \($\bar\delta=-0.92\pm0.01$\). These two values disagree at \($6\sigma$\) and suggest a severe tension for \($f(R)$\) gravity. It remains to be seen whether an improved model of the dwarf galaxies or additional constraints provided by the proper motions of stars measured by future astrometric space missions can return consistent \($\delta$\)'s for the entire sample and remove this tension.
• Anomalous Quasielastic Scattering Contribution in the Centrosymmetric Multi-q Helimagnet SrFeO\($_\mathbf3$\). Andriushin, Nikita D.; Grumbach, Justus; Kulbakov, Anton A.; Tymoshenko, Yuliia V.; Onykiienko, Yevhen A.; Firouzmandi, Reza; Cheng, Erjian; Granovsky, Sergey; Skourski, Yurii; Ollivier, Jacques; Walker, Helen C.; Kocsis, Vilmos; Büchner, Bernd; Keimer, Bernhard; Doerr, Mathias; Inosov, Dmytro S.; Peets, Darren C. (2025). 15(1) 011038.
• Giant quantum oscillations in thermal transport in low-density metals via electron absorption of phonons. Bermond, Baptiste; Wawrzyńczak, Rafał; Zherlitsyn, Sergei; Kotte, Tommy; Helm, Toni; Gorbunov, Denis; Gu, Genda; Li, Qiang; Janasz, Filip; Meng, Tobias; Menges, Fabian; Felser, Claudia; Wosnitza, Joachim; Grushin, Adolfo; Carpentier, David; Gooth, Johannes; Gałeski, Stanisław (2025). 122(10) e2408546122-.

  In metals thermal conductivity is proportional to electrical conductivity and typically of little interest. Here, we have observed giant quantum oscillations in thermal conductivity of the Dirac semimetal ZrTe5, four orders of magnitude larger than expected, even though thermal transport at zero-field is dominated by phonons, which are neutral and thus insensitive to magnetic fields. We identify a generic mechanism for an enhanced absorption of phonons by electrons for metals in quantizing magnetic fields, leading to appearance of quantum oscillations in transport properties of phonons. Our results demonstrate that phonon absorption can be leveraged to reveal other degrees of freedom through their imprint on longitudinal thermal transport of phonons, even if those degrees of freedom have negligible contribution to thermal conductivity. Oscillations of conductance observed in strong magnetic fields are a striking manifestation of the quantum dynamics of charge carriers in solids. The large charge carrier density in typical metals sets the scale of oscillations in both electrical and thermal conductivity, which characterize the Fermi surface. In semimetals, thermal transport at low-charge carrier density is expected to be phonon dominated, yet several experiments observe giant quantum oscillations in thermal transport. This raises the question of whether there is an overarching mechanism leading to sizable oscillations that survives in phonon-dominated semimetals. In this work, we show that such a mechanism exists. It relies on the peculiar phase-space allowed for phonon scattering by electrons when only a few Landau levels are filled. Our measurements on the Dirac semimetal ZrTe5 support this counterintuitive mechanism through observation of pronounced thermal quantum oscillations, since they occur in similar magnitude and phase in directions parallel and transverse to the magnetic field. Our phase-space argument applies to all low-density semimetals, topological or not, including graphene and bismuth. Our work illustrates that phonon absorption can be leveraged to reveal degrees of freedom through their imprint on longitudinal thermal transport.
• Modeling and Analyzing the Influence of Non-Item Pages on Sequential Next-Item Prediction. Fischer, Elisabeth; Zehe, Albin; Hotho, Andreas; Schlör, Daniel (2025).

  Analyzing sequences of interactions between users and items, sequential recommendation models can learn user intent and make predictions about the next item. Next to item interactions, most systems also have interactions with what we call non-item pages: these pages are not related to specific items but still can provide insights into the user’s interests, as, for example, navigation pages. We therefore propose a general way to include these non-item pages in sequential recommendation models to enhance next-item prediction. First, we demonstrate the influence of non-item pages on following interactions using the hypotheses testing framework HypTrails and propose methods for representing non-item pages in sequential recommendation models. Subsequently, we adapt popular sequential recommender models to integrate non-item pages and investigate their performance with different item representation strategies as well as their ability to handle noisy data. To show the general capabilities of the models to integrate non-item pages, we create a synthetic dataset for a controlled setting and then evaluate the improvements from including non-item pages on two real-world datasets. Our results show that non-item pages are a valuable source of information, and incorporating them in sequential recommendation models increases the performance of next-item prediction across all analyzed model architectures.
• Australasian Hydroclimate Response to the Collapse of the Atlantic Meridional Overturning Circulation Under Pre-Industrial and Last Interglacial Climates. Saini, Himadri; Pontes, Gabriel; Brown, Josephine R.; Drysdale, Russell N.; Du, Yanxuan; Menviel, Laurie (2025). 40(3) e2024PA004967.

  Abstract Abrupt climate change events during the last glacial period and the Last Interglacial (LIG) resulted from changes in the Atlantic Meridional Overturning Circulation (AMOC). Over the last 50 years, there is some evidence that the AMOC has weakened, and it is projected to weaken further or even collapse this century driven by the increase in atmospheric greenhouse gases. However, the impact of an AMOC weakening on Australasian hydroclimate is still unclear, particularly under a climate warmer than the pre-industrial (PI). Using the ACCESS-ESM1.5 model, we assess the processes impacting seasonal hydroclimate in the Australasian region in response to an AMOC shutdown under PI and the LIG climatic conditions. While the broad hydroclimate response to an AMOC shutdown is similar in both experiments, notable regional differences emerge, highlighting the influence of background climate states. During austral summer (DJF), the AMOC shutdown leads to drier conditions over the Maritime Continent between 5° \\($5^\circ\$\)S and 6° \\($6^\circ\$\)N and increased precipitation over northern Australia under both PI and LIG conditions. However, the precipitation increase over Australia is weaker under PI than LIG. During austral winter (JJA), mid to high southern regions of Australia and New Zealand experience drying in response to the AMOC shutdown under PI boundary conditions, while under LIG boundary conditions, only southeastern Australia and New Zealand exhibit drier conditions, with northwestern Australia displaying wetter conditions. These results underscore the complex and region-specific responses of Australasian hydroclimate to AMOC disruptions, highlighting the importance of considering background climate states when assessing such impacts.
• Netzwerkmodellierung mit NER und NEL. Schulbuchforschung an der Schnittstelle zur Infrastruktur. Dombrowski, Fabian; Klaes, Sebastian; Keupp, Corinna; Leitgeb, Johannes; Reul, Christian (2025).
• An atlas of RNA-dependent proteins in cell division reveals the riboregulation of mitotic protein-protein interactions. Rajagopal, Varshni; Seiler, Jeanette; Nasa, Isha; Cantarella, Simona; Theiss, Jana; Herget, Franziska; Kaifer, Bianca; Klostermann, Melina; Will, Rainer; Schneider, Martin; Helm, Dominic; König, Julian; Zarnack, Kathi; Diederichs, Sven; Kettenbach, Arminja N; Caudron-Herger, Maïwen (2025). 16(1) 2325–2325.

  Ribonucleoprotein complexes are dynamic assemblies of RNA with RNA-binding proteins, which modulate the fate of RNA. Inversely, RNA riboregulates the interactions and functions of the associated proteins. Dysregulation of ribonucleoprotein functions is linked to diseases such as cancer and neurological disorders. In dividing cells, RNA and RNA-binding proteins are present in mitotic structures, but their impact on cell division remains unclear. By applying the proteome-wide R-DeeP strategy to cells synchronized in mitosis versus interphase integrated with the RBP2GO knowledge, we provided an atlas of RNA-dependent proteins in cell division, accessible at R-DeeP3.dkfz.de. We uncovered AURKA, KIFC1 and TPX2 as unconventional RNA-binding proteins. KIFC1 was identified as a new substrate of AURKA, and new TPX2-interacting protein. Their pair-wise interactions were RNA dependent. In addition, RNA stimulated AURKA kinase activity and stabilized its conformation. In this work, we highlighted riboregulation of major mitotic factors as an additional complexity level of cell division.
• Introducing a computationally light approach to estimate forest height and fractional canopy cover from Sentinel-2 data. Fakhra, Arvin; Latifi, Hooman; Samani, Kyumars Mohammadi; Fassnacht, Fabian Ewald (2025). 228
• Psychosocial Work Factors, Job Stress, and Self-Rated Health Among Hotel Housekeepers. García-Buades, M Esther; Montañez-Juan, Maribel; Blahopoulou, Joanna; Ortiz-Bonnin, Silvia; Chela-Alvarez, Xènia; Bulilete, Oana; Llobera, Joan (2025). 73(3) 116–130.

  BACKGROUND: Hotel housekeeping is widely recognized as a poor-quality job due to its high demands and limited resources. Hotel housekeepers (HHs) face both hard physical work and mentally demanding conditions, yet psychosocial factors in this feminized and precarious occupation remain under-researched. To address this gap, this study examines HHs' exposure to psychosocial factors at work and their impact on job stress and self-rated health. METHODS: A cross-sectional survey of a random sample of 926 HHs in the Balearic Islands (Spain) assessed job stress, self-rated health, psychosocial factors (job demands and resources), and sociodemographic variables using the Copenhagen Psychosocial Questionnaire II (COPSOQ-II) and the National Health Survey. Descriptive analysis and hierarchical linear regression models were applied. RESULTS: The prevalence of job stress was 61.1% (95% confidence interval [CI] = [57.8%, 64.1%]), while the prevalence of poor self-rated health was 59.9% (95% CI = [56.6%, 62.9%]). Hotel housekeepers were highly exposed to job demands such as intense work pace, job-specific stressors, work-life conflict, and emotional demands; highly available job resources were role clarity, task meaning, and social support. Regression models revealed work pace, work-life conflict, nationality, and weak leader support as key predictors of job stress; and work-life conflict and leadership quality as key predictors of self-rated health. CONCLUSION/APPLICATION TO PRACTICE: Although considered an eminently physical job, psychosocial work factors play a key role in explaining HHs' job stress and self-rated health. Occupational health professionals should design workplace interventions to reduce work pace, mitigate work-life conflict, and enhance resources such as leader support, sense of community, and leadership quality.
• Usefulness of body and visceral fat determined by bioimpedancemetry versus body mass index and waist circumference in the identification of elevated values of different atherogenesis risk scales. Gordito Soler, María; Ramírez-Manent, José Ignacio; Tárraga López, Pedro Juan; Martínez-Almoyna Rifá, Emilio; Paublini, Hernán; López González, Ángel Arturo (2025). 500772–500772.

  INTRODUCTION: Obesity and atherogenesis are two highly prevalent pathological processes worldwide that also share several pathophysiological mechanisms. OBJECTIVES: Descriptive and cross-sectional study in 8,590 Spanish workers (4,104 men and 4,486 women) with an average age of 41.5years, in which the usefulness of four scales of overweight and obesity such as body mass index (BMI), waist circumference and percentages of body and visceral fat determined by bioimpedance measurement to identify high levels of atherogenic risk determined by atherogenic dyslipidemia (AD), lipid triad (LT) and several atherogenic indices is assessed. RESULTS: All the overweight and obesity scales show a predictive value between moderate and good, determined by the AUC of the ROC curves, with values ranging from 0.727 to 0.886 in women and 0.676 to 0.885 in men. Of all of them, the one with the highest AUC is visceral fat with values exceeding 0.800 and the lowest are for BMI. In all cases, the AUC is higher in women. CONCLUSIONS: The overweight and obesity scales analysed (BMI, waist circumference and percentage of body and visceral fat) show AUCs for predicting atherogenic risk between moderate and high, with visceral fat being the most useful of all.
• Why Students Are Disruptive and Disengaged in Learning. Matteson, Harlen (2025, March).

  Classroom disruptions and student disengagement are persistent challenges in education. While many educators attribute these issues to lack of discipline or motivation, deeper psychological, social, and environmental factors contribute to the problem. This paper explores the underlying reasons why students disrupt class and appear uninterested in learning, examining issues such as lack of engagement, social pressures, fear of failure, and the effectiveness of traditional teaching methods. It also discusses potential strategies to improve student engagement and reduce disruptive behavior through interactive learning, stronger teacher-student relationships, and addressing students’ social-emotional needs.
• Trial by FIRE: Probing the dark matter density profile of dwarf galaxies with GraphNPE. Nguyen, Tri; Read, Justin; Necib, Lina; Mishra-Sharma, Siddharth; Faucher-Giguère, Claude-André; Wetzel, Andrew (2025).
• S4D-Bio Audio Monitoring of Bone Cement Disintegration in Pulsating Fluid Jet Surgery under Laboratory Conditions. Schaller, Melanie; Hloch, Sergej; Nag, Akash; Klichova, Dagmar; Janssen, Nick; Pude, Frank; Zelenak, Michal; Rosenhahn, Bodo (2025).
• Pulsating Waterjet Cutting Dataset. Schaller, Melanie (2025).
• Load Balanced Attack Defense System with Lightweight Authentication and Modified Blockchain in SDN for B5G. Abdulqadder, Ihsan H.; Aziz, Israa T. N. Meghanathan (ed.) (2025). (Vol. 17) 81–99.

  The involvement of unauthorized packets in Software Defined Networks (SDN) has raised the demand for security. These days, users can access the Internet of Things (IoT) wirelessly over long distances with the use of mobility, and handover. Due to changes in connectivity, the mobility feature is the main reason to permit unauthorized packets. This article uses handover authentication and a modified blockchain to overcome the security issue named LLModBloc. The 5G users are initially authenticated by the edge layer access points (APs) using a hash produced by the lightweight QUARK algorithm using identity and pseudo-ID. The likelihood determines the user's handover if there are too many users connecting to the same AP. A directed acyclic graph (DAC), Harris Hawks Optimization (HHO), and two-level packet based on hexa-features are used in this work. Based on packet characteristics, the capsule network initially divides packets into three categories: normal, suspect, and malicious. Suspicious packets are analyzed using user behavior features and a Q-learning algorithm. Many packets and behavior features were examined. The proposed LLModBlocare evaluated in several metrics such as packet loss, processing time, response time, bandwidth, and latency.The results demonstrate the effectiveness of the proposed system, showing that it outperforms other approaches in terms of network-specific parameters.
• Homological mirror symmetry for projective K3 surfaces. Hacking, Paul; Keating, Ailsa (2025).
• Lipid Profiles After Changes in Alcohol Consumption Among Adults Undergoing Annual Checkups. Suzuki, Takahiro; Fukui, Sho; Shinozaki, Tomohiro; Asano, Taku; Yoshida, Toshiko; Aoki, Jiro; Mizuno, Atsushi (2025). 8(3) e250583.
• kdotpy: k·p theory on a lattice for simulating semiconductor band structures. Beugeling, Wouter; Bayer, Florian; Berger, Christian; Böttcher, Jan; Bovkun, Leonid; Fuchs, Christopher; Hofer, Maximilian; Shamim, Saquib; Siebert, Moritz; Wang, Li-Xian; Hankiewicz, Ewelina; Kießling, Tobias; Buhmann, Hartmut; Molenkamp, Laurens (2025).

  The software project kdotpy provides a Python application for simulating electronic band structures of semiconductor devices with k · p theory on a lattice. The application implements the widely used Kane model, capable of reliable predictions of transport and optical properties for a large variety of topological and non-topological materials with a zincblende crystal structure. The application automates the tedious steps of simulating band structures. The user inputs the relevant physical parameters on the command line, for example materials and dimensions of the device, magnetic field, and temperature. The program constructs the appropriate matrix Hamiltonian on a discretized lattice of spatial coordinates and diagonalizes it. The physical observables are extracted from the eigenvalues and eigenvectors and saved as output. The program is highly customizable with a large set of configuration options and material parameters.
• Probabilistic weather forecasting with machine learning. Price, Ilan; Sanchez-Gonzalez, Alvaro; Alet, Ferran; Andersson, Tom R.; El-Kadi, Andrew; Masters, Dominic; Ewalds, Timo; Stott, Jacklynn; Mohamed, Shakir; Battaglia, Peter; Lam, Remi; Willson, Matthew (2025). 637(8044) 84–90.

  Weather forecasts are fundamentally uncertain, so predicting the range of probable weather scenarios is crucial for important decisions, from warning the public about hazardous weather to planning renewable energy use. Traditionally, weather forecasts have been based on numerical weather prediction (NWP)1, which relies on physics-based simulations of the atmosphere. Recent advances in machine learning (ML)-based weather prediction (MLWP) have produced ML-based models with less forecast error than single NWP simulations2,3. However, these advances have focused primarily on single, deterministic forecasts that fail to represent uncertainty and estimate risk. Overall, MLWP has remained less accurate and reliable than state-of-the-art NWP ensemble forecasts. Here we introduce GenCast, a probabilistic weather model with greater skill and speed than the top operational medium-range weather forecast in the world, ENS, the ensemble forecast of the European Centre for Medium-Range Weather Forecasts4. GenCast is an ML weather prediction method, trained on decades of reanalysis data. GenCast generates an ensemble of stochastic 15-day global forecasts, at 12-h steps and 0.25textdegree latitude--longitude resolution, for more than 80 surface and atmospheric variables, in 8thinspacemin. It has greater skill than ENS on 97.2% of 1,320 targets we evaluated and better predicts extreme weather, tropical cyclone tracks and wind power production. This work helps open the next chapter in operational weather forecasting, in which crucial weather-dependent decisions are made more accurately and efficiently.
• Zum Aufbau digitaler Dramenkorpora. OCR4alltoDraCorTEI als Baustein für die Edition von maschinenlesbaren Versionen historischer Dramendrucke. Dennerlein, Katrin; Rupnig, Martin; Reul, Christian (2025).
• Automatische intratextuelle Analyse von sprachlichen Wiederholungsstrukturen am Beispiel des ‚Marienlebens‘ Philipps von Seitz. Tomasek, Stefan; Hart, Kiara; Schulte, Franziska; Reul, Christian (2025).
• Von der Handschrift zur überlieferungsgeschichtlichen Synopse. HTR zur Erschließung der Überlieferung von Bruder Philipps ‚Marienleben’. Tomasek, Stefan; Reul, Christian; Schulte, Franziska; Hart, Kiara (2025).
• Expression of elongase- and desaturase-encoding genes shapes the cuticular hydrocarbon profiles of honey bees. Rodriguez-León, Daniel Sebastián; Schmitt, Thomas; Pinto, Maria Alice; Thammn, Markus; Scheiner, Ricarda (2025). 6 e17716.

  Most terrestrial insects have a layer of cuticular hydrocarbons (CHCs) protecting them from desiccation and mediating chemical communication. The composition of these hydrocarbons is highly plastic and changes during their lifetime and with environmental conditions. How these changes in CHC composition are achieved is largely unknown. CHC profiles of Apis mellifera honey bees vary among castes, task groups and subspecies adapted to different climates. This makes A. mellifera an excellent model for studying the molecular mechanism underlying CHC biosynthesis. We correlated the expression of specific elongase- and desaturase-encoding genes with the CHC composition in bees performing different social tasks in two highly divergent A. mellifera subspecies. Elongases are enzymes that lengthen the hydrocarbon chain, while desaturases introduce double bonds in it. We evaluated the hypothesis that the expression of the genes encoding these enzymes determines CHC profiles of the worker bees. Our results revealed that the specificity of desaturases and elongases shapes the CHC profiles of worker bees performing different social tasks. Expression of the desaturase-encoding gene LOC100576797 and the elongase-encoding gene LOC550828 seemed to be strongly associated with the abundance of compounds that were characteristic of the CHC profile of nurse bees. In contrast, the compounds that characterised the CHC profiles of the forager bees seemed to be associated with the desaturase-encoding gene LOC551527 and the elongase-encoding gene LOC409638. Our data shed light on the genetic basis for task-specific CHC composition differences in social hymenopterans and paved the ground for unravelling the genetic underpinning of CHC biosynthesis.
• Regularized origin ensemble with a beam prior for range verification in particle therapy with Compton-camera data. Kasprzak, Jona; Roser, Jorge; Werner, Julius; Kohlhase, Nadja; Bolke, Andreas; Kaufmann, Lisa-Marie; Rafecas, Magdalena (2025).
• Cacao grafting increases crop yield without compromising biodiversity. Ocampo‐Ariza, Carolina; Müller, Sophie; Yovera, Fredy; Thomas, Evert; Vansynghel, Justine; Maas, Bea; Steffan‐Dewenter, Ingolf; Tscharntke, Teja (2025). 62(3) 579–592.
• Publizieren im Feedback-Loop. Konzeptionelle Überlegungen zur Analyse des Nutzungsverhaltens bei digitalen Editionen. Esch, Claudia; Hofman, Pia; Klinger, Jana; Herbst, Yannik; Roeder, Torsten; Reul, Christian (2025).
• Coreference in Long Documents using Hierarchical Entity Merging. Gupta, Talika; Hatzel, Hans Ole; Biemann, Chris Y. Bizzoni, S. Degaetano-Ortlieb, A. Kazantseva, S. Szpakowicz (eds.) (2024). 11–17.

  Current top-performing coreference resolution approaches are limited with regard to the maximum length of texts they can accept. We explore a recursive merging technique of entities that allows us to apply coreference models to texts of arbitrary length, as found in many narrative genres. In experiments on established datasets, we quantify the drop in resolution quality caused by this approach. Finally, we use an under-explored resource in the form of a fully coreference-annotated novel to illustrate our model`s performance for long documents in practice. Here, we achieve state-of-the-art performance, outperforming previous systems capable of handling long documents.
• Bone Cement Removal with Audio-Monitoring and Erosion Depth (Dataset). Schaller, Melanie; Hloch, Sergej; Nag, Akash; Klichova, Dagmar; Janssen, Nick; Pude, Frank; Zelenak, Michal; Rosenhahn, Bodo (2024).
• Fault Detection for Agents in Power Grid Topology Optimization: A Comprehensive Analysis. Lehna, Malte; Hassouna, Mohamed; Degtyar, Dmitry; Tomforde, Sven; Scholz, Christoph (2024).

  Optimizing the topology of transmission networks using Deep Reinforcement Learning (DRL) has increasingly come into focus. Various DRL agents have been proposed, which are mostly benchmarked on the Grid2Op environment from the Learning to Run a Power Network (L2RPN) challenges. The environments have many advantages with their realistic chronics and underlying power flow backends. However, the interpretation of agent survival or failure is not always clear, as there are a variety of potential causes. In this work, we focus on the failures of the power grid simulation to identify patterns and detect them in advance. We collect the failed chronics of three different agents on the WCCI 2022 L2RPN environment, totaling about 40k data points. By clustering, we are able to detect five distinct clusters, identifying common failure types. Further, we propose a multi-class prediction approach to detect failures beforehand and evaluate five different prediction models. Here, the Light Gradient-Boosting Machine (LightGBM) shows the best failure detection performance, with an accuracy of 86%. It also correctly identifies in 91% of the time failure and survival observations. Finally, we provide a detailed feature importance analysis that identifies critical features and regions in the grid.
• Literarische Mündlichkeit und ihre Übersetzung: Bairisch auf Spanisch in Thomas Manns Buddenbrooks. Christl, Joachim (2024). 5 147–206.
• Graph Reinforcement Learning in Power Grids: A Survey. Hassouna, Mohamed; Holzhüter, Clara; Lytaev, Pawel; Thomas, Josephine M.; Sick, Bernhard; Scholz, Christoph (2024). abs/2407.04522
• FengWu-W2S: A deep learning model for seamless weather-to-subseasonal forecast of global atmosphere. Ling, Fenghua; Chen, Kang; Wu, Jiye; Han, Tao; Luo, Jing-Jia; Ouyang, Wanli; Bai, Lei (2024).
• (In)visible by Design: An Analysis of a Domestic Labor Platform. Gruszka, Katarzyna; Pillinger, Anna; Gerold, Stefanie; Theine, Hendrik (2024).

  Abstract Introduction Platform Labor and Invisibility Research Context, Data, and Methods Unpacking (In)visibility Dynamics: Findings and Discussion Conclusion Ethical approval and informed consent statements Declaration of conflicting interests Funding ORCID iDs Footnotes Data availability statement References PDF/EPUB Cite article Share options Information, rights and permissions Metrics and citations Figures and tables Abstract Since the rise of platform labor, food delivery, and ride hailing workers have become a visible part of cityscapes, unlike platform workers in the domestic sector. The invisibilization and economic devaluation of reproductive tasks, especially in the private sphere, has a long history.Although platforms are not likely to yield a radical transformation in this sector, qualitative changes concerning the invisibility of work outsourced by households can be observed. In this contribution, we draw from the analytical framework of (in)visibility of/in platform-mediated work and map it against our research findings on a key platform in domestic cleaning in Europe, including netnographic data and interviews with workers and clients. Using the framework as a heuristic tool leads us to a more nuanced understanding of (in)visibility in platform-mediated cleaning in perceptible, institutional, and individual terms. Moreover, we argue that the interrelations between these three layers of (in)visibility offer novel insights for making sense of worker organizing and collective action, the practices related to leaving the platform, and the issue of workers’ occupational identity of domestic cleaners. As such, the study contributes to the current debates on platform labor and domestic work, including the value-visibility relation and the role of digital platforms therein.
• Molecular Beam Epitaxy of Homogeneous Topological HgTe on Doped InAs Substrate. Biswas, Mahitosh; Fürst, Lena; Kamp, Martin; Schreyeck, Steffen; Buhmann, Hartmut; Molenkamp, Laurens W. (2024). 35(3)

  HgTe has been considered to be one of the most versatile topological materials. Depending on the in-plane strain, Weyl and Dirac semi-metal, as well as topological insulator phases, are feasible. Here, for the first time it is reported, that an InAs:S substrate promotes an initial 2D growth of a ZnTe thin layer and subsequent high crystalline quality ZnTe/CdTe superlattices serve as a smooth and continuous virtual substrate for the growth of (Cd,Hg)Te/HgTe/(Cd,Hg)Te heterostructures with unstrained quantum well HgTe (topological insulator) and compressively strained bulk HgTe (Weyl semimetal) by molecular beam epitaxy. Compared with the superlattices previously grown on GaAs substrates, the quantum well and bulk heterostructures exhibit homogeneous surfaces with root mean square roughnesses of 0.88–0.93 nm, which is three times lower than those observed for 3D islands (2.7–3.4 nm) on GaAs substrates. Additionally, magnetotransport measurements confirm high electronic quality and demonstrate that the S-doped InAs substrate can be used as an effective back gate. These results manifest a (big) step forward toward the improvement of micro- and nanometer-sized top- and back-gated device fabrication on topological materials.
• Overlapping top gate electrodes based on low temperature atomic layer deposition for nanoscale ambipolar lateral junctions. Fuchs, Christopher; Fürst, Lena; Buhmann, Hartmut; Kleinlein, Johannes; Molenkamp, Laurens W (2024). 8(2) 025001.

  We present overlapping top gate electrodes for the formation of gate defined lateral junctions in semiconducting layers as an alternative to the back gate/top gate combination and to the split gate configuration. The optical lithography microfabrication of the overlapping top gates is based on multiple layers of low-temperature atomic layer deposited hafnium oxide, which acts as a gate dielectric and as a robust insulating layer between two overlapping gate electrodes exhibiting a large dielectric breakdown field of . The advantage of overlapping gates over the split gate approach is confirmed in model calculations of the electrostatics of the gate stack. The overlapping gate process is applied to Hall bar devices of mercury telluride in order to study the interaction of different quantum Hall states in the nn′, np, pn and pp′ regime.
• ModeConv: A Novel Convolution for Distinguishing Anomalous and Normal Structural Behavior. Schaller, Melanie; Schlör, Daniel; Hotho, Andreas (2024).
• A study of the Behavior of Floating-Point Errors. Damouche, Nasrine (2024).

  The dangers of programs performing floating-point computations are well known. This is due to numerical reliability issues resulting from rounding errors arising during the computations. In general, these round-off errors are neglected because they are small. However, they can be accumulated and propagated and lead to faulty execution and failures. Typically, in critical embedded systems scenario, these faults may cause dramatic damages (eg. failures of Ariane 5 launch and Patriot Rocket mission). The ufp (unit in the first place) and ulp (unit in the last place) functions are used to estimate maximum value of round-off errors. In this paper, the idea consists in studying the behavior of round-off errors, checking their numerical stability using a set of constraints and ensuring that the computation results of round-off errors do not become larger when solving constraints about the ufp and ulp values.
• Global Vegetation Modeling With Pre-Trained Weather Transformers. Janetzky, Pascal; Gallusser, Florian; Hentschel, Simon; Hotho, Andreas; Krause, Anna (2024).
• A machine learning model that outperforms conventional global subseasonal forecast models. Chen, Lei; Zhong, Xiaohui; Li, Hao; Wu, Jie; Lu, Bo; Chen, Deliang; Xie, Shang-Ping; Wu, Libo; Chao, Qingchen; Lin, Chensen; Hu, Zixin; Qi, Yuan (2024). 15(1) 6425.

  Skillful subseasonal forecasts are crucial for various sectors of society but pose a grand scientific challenge. Recently, machine learning-based weather forecasting models outperform the most successful numerical weather predictions generated by the European Centre for Medium-Range Weather Forecasts (ECMWF), but have not yet surpassed conventional models at subseasonal timescales. This paper introduces FuXi Subseasonal-to-Seasonal (FuXi-S2S), a machine learning model that provides global daily mean forecasts up to 42 days, encompassing five upper-air atmospheric variables at 13 pressure levels and 11 surface variables. FuXi-S2S, trained on 72 years of daily statistics from ECMWF ERA5 reanalysis data, outperforms the ECMWF's state-of-the-art Subseasonal-to-Seasonal model in ensemble mean and ensemble forecasts for total precipitation and outgoing longwave radiation, notably enhancing global precipitation forecast. The improved performance of FuXi-S2S can be primarily attributed to its superior capability to capture forecast uncertainty and accurately predict the Madden-Julian Oscillation (MJO), extending the skillful MJO prediction from 30 days to 36 days. Moreover, FuXi-S2S not only captures realistic teleconnections associated with the MJO but also emerges as a valuable tool for discovering precursor signals, offering researchers insights and potentially establishing a new paradigm in Earth system science research.
• Kinetic Cities: Viability of Adaptable PNP Container Modules for Smart Living. Spencer, Constance (2024). 11(2) 1–14.

  The US is experiencing a housing crisis, especially for first time buyers, low income and baby boomers, as well as globally in areas hit by natural disasters due to changing weather systems. Contributing factors to this issue include the slow rebound of housing production from the last recession as well as the recent Covid pandemic market rush to the suburbs, which has resulted in climbing prices and low housing availability (Joint Center, 2019, Spencer, 2021). One possible solution for these consumers would be a container house, but until recently this tiny house option meant that the homeowner would most likely be skirting by-laws since it is often illegal to build small dwellings in many municipalities. Few states or cities have yet created the innovative zoning necessary to address this new phenomenon in their land planning and building codes. In addition, the younger generations want environmentally friendly products and energy efficient homes, something that traditional house developers adopt in limited ways, but small house builders consider integral to their products.
• Advances and prospects of deep learning for medium-range extreme weather forecasting. Olivetti, L.; Messori, G. (2024). 17(6) 2347–2358.
• Graphite/h-BN van der Waals heterostructure as a gate stack for HgTe quantum wells. Liang, Xianhu; Shamim, Saquib; Chen, Dongyun; Fürst, Lena; Taniguchi, Takashi; Watanabe, Kenji; Buhmann, Hartmut; Kleinlein, Johannes; Molenkamp, Laurens W (2024). 35(34) 345001.
• Targeted Adversarial Attacks on Wind Power Forecasts. Heinrich, René; Scholz, Christoph; Vogt, Stephan; Lehna, Malte (2023). 113(2) 863–889.

  In recent years, researchers proposed a variety of deep learning models for wind power forecasting. These models predict the wind power generation of wind farms or entire regions more accurately than traditional machine learning algorithms or physical models. However, latest research has shown that deep learning models can often be manipulated by adversarial attacks. Since wind power forecasts are essential for the stability of modern power systems, it is important to protect them from this threat. In this work, we investigate the vulnerability of two different forecasting models to targeted, semi-targeted, and untargeted adversarial attacks. We consider a Long Short-Term Memory (LSTM) network for predicting the power generation of individual wind farms and a Convolutional Neural Network (CNN) for forecasting the wind power generation throughout Germany. Moreover, we propose the Total Adversarial Robustness Score (TARS), an evaluation metric for quantifying the robustness of regression models to targeted and semi-targeted adversarial attacks. It assesses the impact of attacks on the model's performance, as well as the extent to which the attacker's goal was achieved, by assigning a score between 0 (very vulnerable) and 1 (very robust). In our experiments, the LSTM forecasting model was fairly robust and achieved a TARS value of over 0.78 for all adversarial attacks investigated. The CNN forecasting model only achieved TARS values below 0.10 when trained ordinarily, and was thus very vulnerable. Yet, its robustness could be significantly improved by adversarial training, which always resulted in a TARS above 0.46.
• Managing power grids through topology actions: A comparative study between advanced rule-based and reinforcement learning agents. Lehna, Malte; Viebahn, Jan; Marot, Antoine; Tomforde, Sven; Scholz, Christoph (2023). 14 100276.

  The operation of electricity grids has become increasingly complex due to the current upheaval and the increase in renewable energy production. As a consequence, active grid management is reaching its limits with conventional approaches. In the context of the Learning to Run a Power Network (L2RPN) challenge, it has been shown that Reinforcement Learning (RL) is an efficient and reliable approach with considerable potential for automatic grid operation. In this article, we analyse the submitted agent from Binbinchen and provide novel strategies to improve the agent, both for the RL and the rule-based approach. The main improvement is a N-1 strategy, where we consider topology actions that keep the grid stable, even if one line is disconnected. More, we also propose a topology reversion to the original grid, which proved to be beneficial. The improvements are tested against reference approaches on the challenge test sets and are able to increase the performance of the rule-based agent by 27%. In direct comparison between rule-based and RL agent we find similar performance. However, the RL agent has a clear computational advantage. We also analyse the behaviour in an exemplary case in more detail to provide additional insights. Here, we observe that through the N-1 strategy, the actions of both the rule-based and the RL agent become more diversified.
• A comprehensive review and recent advances in dry mineral classification. Pukkella, Arjun Kumar; Cilliers, Jan J.; Hadler, Kathryn (2023). 201 108208.

  Dry particle classification is an important step in dry particle processing. A thorough literature review is conducted on the available dry particle classification technologies. A detailed discussion is presented on each class of equipment based on the active forces (including centrifugal, gravity, and inertial) that cause particle segregation. Special attention is given to centrifugal classifiers because of their adaptability to a wide range of cut sizes and high throughputs. Interestingly, literature studies on gas cyclones show that they are conventionally used as gas-solid separators with cut sizes d50 less than 3 μm rather than as a particle classifier. Further, throughput rate and cut size (d50) data were collated for all the equipment reviewed. A new graphical illustration of throughput rate vs cut size is used to identify the major gaps in dry classification technology and to recommend research directions.
• Koreni multikulturalnosti Bosne u franjevačkom redu za vreme bosanskih banova. Technical Report (PhD dissertation), Vujković Šakanović, Ana PhD thesis, Novi Sad. (2023).
• Liquor-HGNN: A heterogeneous graph neural network for leakage detection in water distribution networks. Schaller, Melanie; Steininger, Michael; Dulny, Andrzej; Schlör, Daniel; Hotho, Andreas (2023).
• Vlasi Vilićani (Vlasi Usorci). Agić, Admir (2022, November).
• Prilozi prosopografiji Radivojevića – Jurjevića – Pavlovića – Petrovića. Kurtović, Esad (2021). 97–121.
• Bosanska država u odjecima događaja iz 1373. godine. Đulović, Amar (2021). 93–123.
• Bosanska vlastela u XV veku : prospografska studija Rudić Srdjan; Rastović Aleksandar (2021). Istorijski Institut Beograd ; Univerzitet u Banjoj Luci, Beograd, Banja Luka.
• Neka razmatranja o Vlatkovićima, Krajini i Zaostrogu. Isailović, Neven; Jakovljević, Aleksandar (2021). 139–177.
• Matične knjige krštenih katoličkih župa Uskoplja odnosno Skopja od 1745. do 1883. godine Škegro, Ante (2021). Hrvatski institut za povijest, Zagreb.
• Handbuch Sozialwissenschaftliche Gedächtnisforschung Berek, Mathias; Chmelar, Kristina; Dimbath, Oliver; Haag, Hanna; Heinlein, Michael; Leonhard, Nina; Rauer, Valentin; Sebald, Gerd (2020). Springer VS, Wiesbaden.

  Das Handbuch bietet einen umfassenden Überblick über die Grundbegriffe, Theorien und Felder der sozialwissenschaftlichen Gedächtnisforschung.
• Mythos. Corsten, Michael; Jafke, Larissa M. Berek, K. Chmelar, O. Dimbath, H. Haag, M. Heinlein, N. Leonhard, V. Rauer, G. Sebald (eds.) (2020). 97–108.

  Mythos wird hier als kollektiver Bezugsraum der narrativen Symbolisierung von Gesellschaft aufgefasst. Obwohl der Mythos sich der Differenz wahr/falsch entzieht, besitzt er als Form des kollektiven Wissens und sozialen Gedächtnisses eine konstitutive Funktion für gesellschaftliche Ordnungsbildung. Der Beitrag untersucht dazu drei theoretische Aspekte des Mythos (Abschn. 2.1–2.3) und stellt die Bedeutung des Mythenkonzepts für vier Forschungsfelder vor: (Abschn. 3.1) Familie und Kindheit, (Abschn. 3.2) Bildung, (Abschn. 3.3) (Populäre Kultur) und (Abschn. 3.4) Politik.
• Colluding with the Infidel: The Alliance between Ladislaus of Naples and the Turks. Filipović, Emir O. (2019). 8(2) 361–389.
• A Xgboost Risk Model Via Feature Selection and Bayesian Hyper-Parameter Optimization. Wang, Yan; Ni, Xuelei Sherry (D. Hérin; D. A. Zighed, eds.) (2019). 11(1) 1–17.

  This paper aims to explore models based on the extreme gradient boosting (XGBoost) approach for business risk classification. Feature selection (FS) algorithms and hyper-parameter optimizations are simultaneously considered during model training. The five most commonly used FS methods including weight by Gini, weight by Chi-square, hierarchical variable clustering, weight by correlation, and weight by information are applied to alleviate the effect of redundant features. Two hyper-parameter optimization approaches, random search (RS) and Bayesian tree-structuredParzen Estimator (TPE), are applied in XGBoost. The effect of different FS and hyper-parameter optimization methods on the model performance are investigated by the Wilcoxon Signed Rank Test. The performance of XGBoost is compared to the traditionally utilized logistic regression (LR) model in terms of classification accuracy, area under the curve (AUC), recall, and F1 score obtained from the 10-fold cross validation. Results show that hierarchical clustering is the optimal FS method for LR while weight by Chi-square achieves the best performance in XG-Boost. Both TPE and RS optimization in XGBoost outperform LR significantly. TPE optimization shows a superiority over RS since it results in a significantly higher accuracy and a marginally higher AUC, recall and F1 score. Furthermore, XGBoost with TPE tuning shows a lower variability than the RS method. Finally, the ranking of feature importance based on XGBoost enhances the model interpretation. Therefore, XGBoost with Bayesian TPE hyper-parameter optimization serves as an operative while powerful approach for business risk modeling
• Migracijski tokovi, društveno-političke prilike u Bosanskom ejaletu (1683.-1718.). Technical Report (PhD dissertation), Smajić, Ramiza PhD thesis, Zagreb. (2019). 262.
• RANDOMIZED STEGANOGRAPHY IN SKIN TONE IMAGES. K, Ashita; P, Smitha Vas (A. K; S. V. P, eds.) (2018). 8(3) 1–8.

  Steganography is the technique of hiding a confidential message in an ordinary message and the extraction of that secret message at its destination. Different carrier file formats can be used in steganography. Among these carrier file formats, digital images are the most popular. For this work, digital images are used. Here steganography is done on the skin portion of an image. First skin portion of an image is detected. Random pixels are selected from that detected region using a pseudo-random number generator. The bits of the secret message will be embedded on the LSB of these random pixels. An analysis is done to check the efficiency and robustness of the proposed method. The aim of this work is to show that steganography done using random pixel selection is less prone to outside attacks.
• Poljica u srednjem vijeku. Technical Report (Master thesis), Bulić, Ana PhD thesis, Sveučilište Jurja Dobrile u Puli ; Filozofski fakultet. (2018).
• Edge Detection Algorithm for Yoruba Character Recognition. S.A, Yekeen; T.S, Ibiyemi (2018). 5(1)

  Digital image processing for pattern recognition involves several processing and pre-processing steps. Edge detection stands a great position for accurate pattern recognition most especially in character recognition system. Many edge detection techniques were implemented with convolution mask and based on approximations to differential operators. For efficient Yoruba character recognition, compass edge detection algorithm was developed to enhance the recognition rate of Yoruba character. The algorithm developed achieved 0.923 edge detection error rate. The level of accuracy will have been better if noise removal or reduction steps were included in the algorithm.
• Bračne veze bosanske vlastele. Rudić, Srđan (2018). 18 173–188.
• Coir Cake. Coir, We (W. Coir, ed.) (2012).
• Matične knjige umrlih uskopaljskih župa (od 1755. do 1883. godine) Škegro, Ante (2012). 505. Hrvatski institut za povijest, Zagreb.
• ACTIVE CONTROLLER DESIGN FOR THE GENERALIZED PROJECTIVE SYNCHRONIZATION OF DOUBLE-SCROLL CHAOTIC SYSTEMS. Vaidyanathan1, Sundarapandian; Pakiriswamy, and Sarasu (2012).
• Prilog poznavanju nekih islamizovanih bosanskih porodica. Rudić, Srđan S. Rudić (ed.) (2011). 425–439.
• Stanford’s Multi-Pass Sieve Coreference Resolution System at the CoNLL-2011 Shared Task. Lee, Heeyoung; Peirsman, Yves; Chang, Angel; Chambers, Nathanael; Surdeanu, M.; Jurafsky, Dan (2011).
• A High-Performance Syntactic and Semantic Dependency Parser. Björkelund, Anders; Bohnet, Bernd; Hafdell, Love; Nugues, Pierre Y. Liu, T. Liu (eds.) (2010). 33–36.
• Top Accuracy and Fast Dependency Parsing is not a Contradiction. Bohnet, Bernd C.-R. Huang, D. Jurafsky (eds.) (2010). 89–97.
• Introduction to air classification. DeCenso, A. J. (2009).

  Air classifiers are preferred over fine screening in one or both of the following situations: 1) the rate is too high for fine screening; 2) the cut point is too fine for screening. Take for example an application in which calcium carbonate must be separated at 75 microns. A common round vibrating separator with a 200 mesh screen can make a very sharp separation in such an application at about 1 tn/hr. But what if the desired processing rate is 30 tn/hr? Sure, you could install 30 vibrating screens, but that’s not really practical. A single air classifier could handle the entire 30 tn/hr.
• Air Classifying. Furchner, Bodo; Zampini, Stefano (2009).

  Abstract Air classification is a process for the dry separation of a disperse phase according to the particle size, particle shape, or density, or, more precisely, the settling velocity. The settling velocity results from the balance of forces between the mass force and the drag force for every single particle. In a vertical gravity classifier particles move to the fine fraction if their settling velocity is lower than the air velocity, and to the coarse fraction if their settling velocity is higher than the air velocity. Particles in a deflector wheel behave similarly. The settling velocity must be calculated with the centrifugal acceleration in this case. Coarse classification in the range of 0.2 – 10 mm particle size is performed by gravity classifiers. Fine classification is generally performed in classifiers with deflector wheels. The fineness is adjusted by means of the speed of the wheel; increasing speed increases the centrifugal force and settling velocity. Fineness values of deflector wheel classifiers range from 1 to 200 µm. A peripheral speed of up to 150 m/s is used for finest products. Air classification is widely used in many industries and for many applications from laboratory scale to large-scale processing. 1. Introduction 2. General Principles 2.1. Equilibrium of Forces at Individual Particles 2.1.1. Classifying in the Gravitational Field 2.1.2. Classifying in a Centrifugal Field 2.2. Separation of Bulk Material 2.3. Energy Requirement for Air Classifying 3. Machines for Air Classification 3.1. Gravity Classifiers 3.2. Inertial Classifiers 3.3. Internal Recirculation Air Classifiers 3.4. Deflector-Wheel Classifiers 3.5. Classifier Mills 4. Application Examples for Air Classification 4.1. Cement 4.2. Fillers 4.3. Protein Shifting 4.4. Toner
• Uniqueness of enhancement for triangulated categories. Lunts, Valery A.; Orlov, Dmitri O. (2009).
• Razmišljanje o ranim banovima Bosne i neke pretpostavke o njihovom poreklu i pokušaj uspostavljanja rodoslova. Andrejić, Živojin (2007). 5 105–132.
• Povelja kralja Stefana Dabiše braći Semković:1395, 17. maj. Rudić, Srđan (2006). 5 157–171.
• Na klizištu povijesti : sveta kruna ugarska i sveta kruna bosanska 1387-1463 Lovrenović Dubravko (2006). Synopsis, Zagreb.
• Granica između Splita i Poljica i splitsko-poljički sukobi u XIV. i XV. stoljeću (Dio prvi: Teritorijalna rasprostranjenost Poljica i politički okvir splitsko poljičkih odnosa u XIV. i XV. stoljeću). Nazor, Ante (2002). 20 29–57.
• Dramatični brak (Porodične i političke afere, pa i otvoreno neprijateljstvo između porodica Hrvatinića i Hranića-Kosača). Kurtović, Esad (2001). 26(134 (45) 73–76.
• Stanovništvo duvanjskog kraja u XVII. i XVIII. stoljeću. Soldo, Josip Ante J. Krišto (ed.) (2000). 159–187.
• Antologija starih bosanskih tekstova Dizdar, Mak in Antologije (Alef (Firm))) (1997). Alef, Sarajevo.
• Sinjska krajina u 17. i 18. stoljeću Soldo, Josip Ante in Sinjska krajina u 17. i 18. stolje’cu (1997). Ogranak Matice Hrvatske, Sinj.
• The idiot Dostoyevsky, Fyodor; Garnett, Constance; Cardinal Agnès (1996). Wordsworth Editions Limited, Ware, Hertfordshire.
• Sinjska krajina u 17. i 18. stoljeću Soldo, Josip Ante in Sinjska krajina u 17. i 18. stoljeću (1995). Matica hrvatska, Sinj.
• Razgraničenje između Bosanskog pašaluka i mletačke Dalmacije nakon kandijskog rata. Buzov, Snježana (1993). 12(12) 1–38.
• MODELING OF REDISTRIBUTION OF INFUSED DOPANT IN A MULTILAYER STRUCTURE DOPANT UNDER INFLUENCE OF VARIATION OF PRESSURE OF VAPOR OF THE DOPANT. Krovetz, Robert; Croft, W. Bruce (1992). 10(2) 115–141.

  Lexical ambiguity is a pervasive problem in natural language processing. However, little quantitative information is available about the extent of the problem or about the impact that it has on information retrieval systems. We report on an analysis of lexical ambiguity in information retrieval test collections and on experiments to determine the utility of word meanings for separating relevant from nonrelevant documents. The experiments show that there is considerable ambiguity even in a specialized database. Word senses provide a significant separation between relevant and nonrelevant documents, but several factors contribute to determining whether disambiguation will make an improvement in performance. For example, resolving lexical ambiguity was found to have little impact on retrieval effectiveness for documents that have many words in common with the query. Other uses of word sense disambiguation in an information retrieval context are discussed.
• Etničke promjene i migracije stanovništva u Sinjskoj krajini krajem 17. i početkom 18. stoljeća. Soldo, Josip Ante (1989). 4 81–133.
• Seoba Ramljaka u Sinjsku krajinu. Soldo, Josip Ante (1988). 38 23–33.
• Marks’ Standard Handbook for Mechanical Engineers Avallone, Eugene A.; Baumeister, Theodore (1987). (Ninth ) McGraw-Hill, New York.
• Sieve analysis, the Cinderella of particle size analysis methods?. Leschonski, Kurt (1979). 24(2) 115–124.
• Confidence intervals vs Bayesian intervals. Jaynes, E. T. (1976). (Vol. II) 175–257.

  For many years, statistics textbooks have followed this 'canonical' procedure: (1) the reader is warned not to use the discredited methods of Bayes and Laplace, (2) an orthodox method is extolled as superior and applied to a few simple problems, (3) the corresponding Bayesian solutions are _not_ worked out or described in any way. The net result is that no evidence whatsoever is offered to substantiate the claim of superiority of the orthodox method. To correct this situation we exhibit the Bayesian and orthodox solutions to six common statistical problems involving confidence intervals (including significance tests based on the same reasoning). In every case, we find that the situation is exactly the opposite; i.e., the Bayesian method is easier to apply and yields the same or better results. Indeed, the orthodox results are satisfactory only when they agree closely (or exactly) with the Bayesian results. No contrary example has yet been produced. By a refinement of the orthodox statistician's own criterion of performance, the best confidence interval for any location or scale parameter is proved to be the Bayesian posterior probability interval. In the cases of point estimation and hypothesis testing, similar proofs have long been known. We conclude that orthodox claims of superiority are totally unjustified; today, the original statistical methods of Bayes and Laplace stand in a position of proven superiority in actual performance, that places them beyond the reach of mere ideological or philosophical attacks. It is the continued teaching and use of orthodox methods that is in need of justification and defense.
• Stećci centralne Bosne Bešlagić, Šefik (1967). 115. Zavod za zaštitu spomenika kulture Bosne i Hercegovine, Sarajevo.
• Naselja i kretanje stanovništva u Poljicama. Jutronić, Andre (1963). 25(1) 37–59.
• Naseljenje starohrvatske Podmorske župe. Katić, Lovre (1960). 3(7) 159–184.
• Inversion of a perfectly elastic spherical shell. Ericksen, J. L. (1955). 35(9-10) 382–385.

  The problem of inversion of a spherical shell which is made of an incompressible, perfectly elastic material is solved in full generality. It is shown that, if the strain energy is of the form assumed in the Mooney-Rivlin theory for rubber, then the surfaces of the deformed shell may be left free of surface tractions.
• Nekoliko isprava iz početka XV st. Šišić, Ferdo (1938). 39 131–320.