Hasil untuk "History of Germany"

Solal Rapaport, Laurent Pautet, Samuel Tardieu et al.

Version Control Systems (VCS) like Git allow developers to locally rewrite recorded history, e.g., to reorder and suppress commits or specific data in them. These alterations have legitimate use cases, but become problematic when performed on public branches that have downstream users: they break push/pull workflows, challenge the integrity and reproducibility of repositories, and create opportunities for supply chain attackers to sneak into them nefarious changes. We conduct the first large-scale investigation of Git history alterations in public code repositories. We analyze 111 M (millions) repositories archived by Software Heritage, which preserves VCS histories even across alterations. We find history alterations in 1.22 M repositories, for a total of 8.7 M rewritten histories. We categorize changes by where they happen (which repositories, which branches) and what is changed in them (files or commit metadata). Conducting two targeted case studies we show that altered histories recurrently change licenses retroactively, or are used to remove ''secrets'' (e.g., private keys) committed by mistake. As these behaviors correspond to bad practices-in terms of project governance or security management, respectively-that software recipients might want to avoid, we introduce GitHistorian, an automated tool, that developers can use to spot and describe history alterations in public Git repositories.

Jacob Tielke, Alessandro Verdecchia, Chelsea L. Pederson et al.

Abstract Geothermal reservoirs commonly record seismic and creep events, constituting earthquake hazards in enhanced geothermal systems. To understand the geological controls on mixed‐mode frictional behaviors in these settings, we performed friction experiments on fault gouges from the polyphase‐altered carbonate Massenkalk Formation in Germany, a regional priority target for geothermal energy production. The experiments, performed at conditions consistent with ∼4 km deep geothermal reservoir, yield evolved friction coefficients of ∼0.48 for limestone and ∼0.61 for dolostone, whereas the silicate‐carbonate fault gouges exhibit ∼0.55. Dolostone gouges exhibit unstable sliding at low displacement rates, whereas the limestone and silicate‐carbonate gouges are stable at all investigated conditions, with the dolostone and silicate‐carbonate samples exhibiting the most significant microstructural strain localization. These results suggest that the geochemical alteration history of geothermal systems may facilitate hybrid frictional behaviors of seismic and aseismic slip within the same reservoir, and that cataclastic strain localization style is independent of frictional behavior.

Filiz Keser Aschenberger

This study examines the life course transitions of five Turkish migrant women in Germany, focusing on the interplay of migration histories, gendered roles, and educational trajectories in shaping their lives. Employing a life course approach and in-depth narrative interviews, the research reveals the persistent challenges experienced in navigating transitions, significantly influenced by intergenerational migration and education. Gendered expectations and familial responsibilities, compounded by structural barriers in education and the labour market, profoundly shaped their educational attainment, career choices, and integration. Limited guidance, language barriers, and family influences created obstacles, further impacted by marriage, motherhood, and caregiving. This research extends the understanding of the lasting influence of migration history and education on the gendered life courses of Turkish women in Germany, emphasizing the need for inclusive policies that address systemic barriers and promote equitable opportunities.

Alexander W. Raymond, Sheperd S. Doeleman, Keiichi Asada et al.

The first very long baseline interferometry (VLBI) detections at 870 μ m wavelength (345 GHz frequency) are reported, achieving the highest diffraction-limited angular resolution yet obtained from the surface of the Earth and the highest-frequency example of the VLBI technique to date. These include strong detections for multiple sources observed on intercontinental baselines between telescopes in Chile, Hawaii, and Spain, obtained during observations in 2018 October. The longest-baseline detections approach 11 G λ , corresponding to an angular resolution, or fringe spacing, of 19 μ as. The Allan deviation of the visibility phase at 870 μ m is comparable to that at 1.3 mm on the relevant integration timescales between 2 and 100 s. The detections confirm that the sensitivity and signal chain stability of stations in the Event Horizon Telescope (EHT) array are suitable for VLBI observations at 870 μ m. Operation at this short wavelength, combined with anticipated enhancements of the EHT, will lead to a unique high angular resolution instrument for black hole studies, capable of resolving the event horizons of supermassive black holes in both space and time.

Mario E. Andina, Alexander Nelde, Christian H. Nolte et al.

Objective: (1) To assess the accuracy of a standard operating procedure (SOP) regarding the utilization of atrial fibrillation (AF) alarms in everyday clinical practice, and (2) to evaluate the performance of automated continuous surveillance for atrial fibrillation (AF) in hospitalized acute stroke patients. Design: Retrospective cohort study. Setting: Two stroke units from two tertiary care hospitals in Berlin, Germany. Participants: We identified 635 patients with ischemic stroke diagnosis for the time period between 01. January and 30. September 2021 of which 176 patients had recorded AF alarms during monitoring. Of those, 115 patients were randomly selected for evaluation. After excluding 6 patients with hemorrhagic stroke in their records, 109 patients (mean age: 79.1 years, median NIHSS at admission: 6, 57% female) remained for analysis. Intervention: Using a clinical data warehouse for comprehensive data storage we retrospectively downloaded and visualized ECG data segments of 65 s duration around the automated AF alarms. We restricted the maximum number of ECG segments to ten per patient. Each ECG segment plot was uploaded into a REDCap database and categorized as either AF, non-AF or artifact by manual review. Atrial flutter was subsumed as AF. These classifications were then matched with 1) medical history and known diseases before stroke, 2) discharge diagnosis, and 3) recommended treatment plan in the medical history using electronic health records. Main outcome measures: The primary outcome was the proportion of previously unknown AF diagnoses correctly identified by the monitoring system but missed by the clinical team during hospitalization. Secondary outcomes included the proportion of patients in whom a diagnosis of AF would likely have led to anticoagulant therapy. We also evaluated the accuracy of the automated detection system in terms of its positive predictive value (PPV). Results: We evaluated a total of 717 ECG alarm segments from 109 patients. In 4 patients (3.7, 95% confidence interval [CI] 1.18–9.68%) physicians had missed AF despite at least one true positive alarm. All four patients did not receive long-term secondary prevention in form of anticoagulant therapy. 427 out of 717 alarms were rated true positives, resulting in a positive predictive value of 0.6 (CI 0.56–0.63) in this cohort. Conclusion: By connecting a data warehouse, electronic health records and a REDCap survey tool, we introduce a path to assess the monitoring quality of AF in acute stroke patients. We find that implemented standards of procedure to detect AF during stroke unit care are effective but leave room for improvement. Such data warehouse-based concepts may help to adjust internal processes or identify targets of further investigations.

Juergen Schmidhuber

Machine learning (ML) is the science of credit assignment. It seeks to find patterns in observations that explain and predict the consequences of events and actions. This then helps to improve future performance. Minsky's so-called "fundamental credit assignment problem" (1963) surfaces in all sciences including physics (why is the world the way it is?) and history (which persons/ideas/actions have shaped society and civilisation?). Here I focus on the history of ML itself. Modern artificial intelligence (AI) is dominated by artificial neural networks (NNs) and deep learning, both of which are conceptually closer to the old field of cybernetics than what was traditionally called AI (e.g., expert systems and logic programming). A modern history of AI & ML must emphasize breakthroughs outside the scope of shallow AI text books. In particular, it must cover the mathematical foundations of today's NNs such as the chain rule (1676), the first NNs (circa 1800), the first practical AI (1914), the theory of AI and its limitations (1931-34), and the first working deep learning algorithms (1965-). From the perspective of 2025, I provide a timeline of the most significant events in the history of NNs, ML, deep learning, AI, computer science, and mathematics in general, crediting the individuals who laid the field's foundations. The text contains numerous hyperlinks to relevant overview sites. With a ten-year delay, it supplements my 2015 award-winning deep learning survey which provides hundreds of additional references. Finally, I will put things in a broader historical context, spanning from the Big Bang to when the universe will be many times older than it is now.

Chenxi Ji

Do we really understand how machine classifies art styles? Historically, art is perceived and interpreted by human eyes and there are always controversial discussions over how people identify and understand art. Historians and general public tend to interpret the subject matter of art through the context of history and social factors. Style, however, is different from subject matter. Given the fact that Style does not correspond to the existence of certain objects in the painting and is mainly related to the form and can be correlated with features at different levels.(Ahmed Elgammal et al. 2018), which makes the identification and classification of the characteristics artwork's style and the "transition" - how it flows and evolves - remains as a challenge for both human and machine. In this work, a series of state-of-art neural networks and manifold learning algorithms are explored to unveil this intriguing topic: How does machine capture and interpret the flow of Art History?

Mancheng Meng, Ziyan Wu, Terrence Chen et al.

Predicting the future trajectory of a person remains a challenging problem, due to randomness and subjectivity of human movement. However, the moving patterns of human in a constrained scenario typically conform to a limited number of regularities to a certain extent, because of the scenario restrictions and person-person or person-object interactivity. Thus, an individual person in this scenario should follow one of the regularities as well. In other words, a person's subsequent trajectory has likely been traveled by others. Based on this hypothesis, we propose to forecast a person's future trajectory by learning from the implicit scene regularities. We call the regularities, inherently derived from the past dynamics of the people and the environment in the scene, scene history. We categorize scene history information into two types: historical group trajectory and individual-surroundings interaction. To exploit these two types of information for trajectory prediction, we propose a novel framework Scene History Excavating Network (SHENet), where the scene history is leveraged in a simple yet effective approach. In particular, we design two components: the group trajectory bank module to extract representative group trajectories as the candidate for future path, and the cross-modal interaction module to model the interaction between individual past trajectory and its surroundings for trajectory refinement. In addition, to mitigate the uncertainty in ground-truth trajectory, caused by the aforementioned randomness and subjectivity of human movement, we propose to include smoothness into the training process and evaluation metrics. We conduct extensive evaluations to validate the efficacy of our proposed framework on ETH, UCY, as well as a new, challenging benchmark dataset PAV, demonstrating superior performance compared to state-of-the-art methods.

Xiaoming Jiang, Peng Zheng, Ismael Soto et al.

Invasive alien gastropods are a particularly pervasive taxonomic group worldwide, often causing substantial impacts on aquatic and terrestrial ecosystems. Yet, much remains unknown about this invasive group’s economic costs to human society. Here, we used the InvaCost database to evaluate the taxonomic, spatial, and temporal patterns of economic costs associated with invasive gastropods on the global scale. In total, 13 species of invasive gastropods caused a cumulative global cost of US$ 3.94 billion over the period 1966–2020, with a majority being attributed to aquatic species ($ 3.72 billion, 94.4 %, concentrated mostly in Asia) and only $ 0.22 billion (5.6 %, concentrated mostly in Europe) to terrestrial species. Among different regions, Asia (3.71 billion) reported the greatest costs, compared to far lower costs reported in Europe (214.50 million), North America (13.80 million), Oceania (2.69 million), South America (<1 million) and Africa (<1 million). The vast majority (94.2 %) of these costs were due to the family Ampullariidae and the genus Pomacea (apple snails) which were largely reported in Asia. Furthermore, 88.4 % of total gastropod-related costs resulted from direct resource damages and losses, being one order of magnitude higher than management related costs (9.0 %). A majority (81.5 %) of total gastropod costs was incurred by agriculture, and relatively little was attributed to authorities and stakeholders (6.3 %), public and social welfare (4.8 %) and mixed (7.3 %) impacted sectors. Average annual costs amounted to $ 71.63 million, most of which ($ 67.64 million) occurred in aquatic environments. Despite the increasing economic losses caused by invasive gastropods, we identified significant knowledge gaps in cost information of many well-known invasive gastropods. Thus, we appeal for further urgently needed research efforts to quantify costs of invasive gastropods to fill the knowledge gaps, in order to better evaluate this group’s true magnitude of monetary costs.

Geza Kovacs

Users' detailed browsing activity - such as what sites they are spending time on and for how long, and what tabs they have open and which one is focused at any given time - is useful for a number of research and practical applications. Gathering such data, however, requires that users install and use a monitoring tool over long periods of time. In contrast, browser extensions can gain instantaneous access months of browser history data. However, the browser history is incomplete: it records only navigation events, missing important information such as time spent or tab focused. In this work, we aim to reconstruct time spent on sites with only users' browsing histories. We gathered three months of browsing history and two weeks of ground-truth detailed browsing activity from 185 participants. We developed a machine learning algorithm that predicts whether the browser window is focused and active at one second-level granularity with an F1-score of 0.84. During periods when the browser is active, the algorithm can predict which the domain the user was looking at with 76.2% accuracy. We can use these results to reconstruct the total time spent online for each user with an R^2 value of 0.96, and the total time each user spent on each domain with an R^2 value of 0.92.

Cornelius Fritz, Emilio Dorigatti, David Rügamer

During 2020, the infection rate of COVID-19 has been investigated by many scholars from different research fields. In this context, reliable and interpretable forecasts of disease incidents are a vital tool for policymakers to manage healthcare resources. Several experts have called for the necessity to account for human mobility to explain the spread of COVID-19. Existing approaches are often applying standard models of the respective research field. This habit, however, often comes along with certain restrictions. For instance, most statistical or epidemiological models cannot directly incorporate unstructured data sources, including relational data that may encode human mobility. In contrast, machine learning approaches may yield better predictions by exploiting these data structures, yet lack intuitive interpretability as they are often categorized as black-box models. We propose a trade-off between both research directions and present a multimodal learning approach that combines the advantages of statistical regression and machine learning models for predicting local COVID-19 cases in Germany. This novel approach enables the use of a richer collection of data types, including mobility flows and colocation probabilities, and yields the lowest MSE scores throughout our observational period in our benchmark study. The results corroborate the necessity of including mobility data and showcase the flexibility and interpretability of our approach.

M. Altmeyer, M. Seeliger, A. Ginau et al.

<p>The current state of research about ancient settlements within the Nile Delta allows the hypothesizing of fluvial connections to ancient settlements all over the Nile Delta. Previous studies suggest a larger Nile branch close to Kom el-Gir, an ancient settlement hill in the northwestern Nile Delta. To contribute new knowledge to this little-known site and prove this hypothesis, this study aims at using small-scale paleogeographic investigations to reconstruct an ancient channel system in the surroundings of Kom el-Gir. The study pursues the following: (1) the identification of sedimentary environments via stratigraphic and portable X-ray fluorescence (pXRF) analyses of the sediments, (2) the detection of fluvial elements via electrical resistivity tomography (ERT), and (3) the synthesis of all results to provide a comprehensive reconstruction of a former fluvial network in the surroundings of Kom el-Gir. Therefore, auger core drillings, pXRF analyses, and ERT were conducted to examine the sediments within the study area. Based on the evaluation of the results, the study presents clear evidence of a former channel system in the surroundings of Kom el-Gir. Thereby, it is the combination of both methods, 1-D corings and 2-D ERT profiles, that derives a more detailed illustration of previous environmental conditions which other studies can adopt. Especially within the Nile Delta which comprises a large number of smaller and larger ancient settlement hills, this study's approach can contribute to paleogeographic investigations to improve the general understanding of the former fluvial landscape.</p>

Solange Arber

Alfredo Garbuno-Inigo, F. Alejandro DiazDelaO, Konstantin M. Zuev

The scientific understanding of real-world processes has dramatically improved over the years through computer simulations. Such simulators represent complex mathematical models that are implemented as computer codes which are often expensive. The validity of using a particular simulator to draw accurate conclusions relies on the assumption that the computer code is correctly calibrated. This calibration procedure is often pursued under extensive experimentation and comparison with data from a real-world process. The problem is that the data collection may be so expensive that only a handful of experiments are feasible. History matching is a calibration technique that, given a simulator, it iteratively discards regions of the input space using an implausibility measure. When the simulator is computationally expensive, an emulator is used to explore the input space. In this paper, a Gaussian process provides a complete probabilistic output that is incorporated into the implausibility measure. The identification of regions of interest is accomplished with recently developed annealing sampling techniques. Active learning functions are incorporated into the history matching procedure to refocus on the input space and improve the emulator. The efficiency of the proposed framework is tested in well-known examples from the history matching literature, as well as in a proposed testbed of functions of higher dimensions.

Hasan Padamsee

Radio frequency (RF) superconductivity has become a key technology for many modern particle accelerators. One of its most salient features of this technology is the ability of superconducting RF cavities to deliver high accelerating gradients in continuous-wave and long-pulse modes of operation. However, reaching the current state of the technology was not an easy fit. Over many years scientists and engineers had to overcome several serous performance limitations. In this paper, I attempt to the best of my knowledge to trace the history of accelerating gradients evolution in the field of superconducting radio frequency. I will restrict the scope to primary innovations along with some of the ensuing developments in developing cavities made of bulk niobium. But I will not cover all the many applications and findings over the subsequent decades of progress that were based on the primary discoveries and inventions. I will also not cover a number of other important topics in the history of cavity developments, such as the drive for higher Q values, or the push for lower cavity costs via Nb/Cu cavities or large grain Nb cavities.

Carla J. Harper, Edith L. Taylor, Michael Krings

Permineralized peat from the central Transantarctic Mountains of Antarctica has provided a wealth of information on plant and fungal diversity in Middle Triassic high-latitude forest paleoecosystems; however, there are no reports as yet of algae or cyanobacteria. The first record of a fossil filamentous cyanobacterium in this peat consists of wide, uniseriate trichomes composed of discoid cells up to 25 µm wide, and enveloped in a distinct sheath. Filament morphology, structurally preserved by permineralization and mineral replacement, corresponds to the fossil genus Palaeo-lyngbya, a predominantly Precambrian equivalent of the extant Lyngbya sensu lato (Oscillatoriaceae, Oscillatoriales). Specimens occur exclusively in masses of interwoven hyphae produced by the fungus Endochaetophora antarctica, suggesting that a special micro-environmental setting was required to preserve the filaments. Whether some form of symbiotic relationship existed between the fungus and cyanobacterium remains unknown.

G. Aad, B. Abbott, D.C. Abbott et al.

Azimuthal anisotropies of muons from charm and bottom hadron decays are measured in Pb+Pb collisions at sNN=5.02TeV. The data were collected with the ATLAS detector at the Large Hadron Collider in 2015 and 2018 with integrated luminosities of 0.5nb−1 and 1.4nb−1, respectively. The kinematic selection for heavy-flavor muons requires transverse momentum 4<pT<30GeV and pseudorapidity |η|<2.0. The dominant sources of muons in this pT range are semi-leptonic decays of charm and bottom hadrons. These heavy-flavor muons are separated from light-hadron decay muons and punch-through hadrons using the momentum imbalance between the measurements in the tracking detector and in the muon spectrometers. Azimuthal anisotropies, quantified by flow coefficients, are measured via the event-plane method for inclusive heavy-flavor muons as a function of the muon pT and in intervals of Pb+Pb collision centrality. Heavy-flavor muons are separated into contributions from charm and bottom hadron decays using the muon transverse impact parameter with respect to the event primary vertex. Non-zero elliptic (v2) and triangular (v3) flow coefficients are extracted for charm and bottom muons, with the charm muon coefficients larger than those for bottom muons for all Pb+Pb collision centralities. The results indicate substantial modification to the charm and bottom quark angular distributions through interactions in the quark-gluon plasma produced in these Pb+Pb collisions, with smaller modifications for the bottom quarks as expected theoretically due to their larger mass.

Maria Clara Iruzun Martins, Travis Park, Rachel Racicot et al.

In morphological traits, variation within species is generally considered to be lower than variation among species, although this assumption is rarely tested. This is particularly important in fields like palaeontology, where it is common to use a single individual as representative of a species due to the rarity of fossils. Here, we investigated intraspecific variation in the cochleae of harbour porpoises (Phocoena phocoena). Interspecific variation of cochlear morphology is well characterised among odontocetes (toothed whales) because of the importance of the structure in echolocation, but generally these studies use only a single cochlea to represent each species. In this study we compare variation within the cochleae of 18 specimens of P. phocoena with variations in cochlear morphology across 51 other odontocete species. Using both 3D landmark and linear measurement data, we performed Generalised Procrustes and principal component analyses to quantify shape variation. We then quantified intraspecific variation in our sample of P. phocoena by estimating disparity and the coefficient of variation for our 3D and linear data respectively. Finally, to determine whether intraspecific variation may confound the results of studies of interspecific variation, we used multivariate and univariate analyses of variance to test whether variation within the specimens of P. phocoena was significantly lower than that across odontocetes. We found low levels of intraspecific variation in the cochleae of P. phocoena, and that cochlear shape within P. phocoena was significantly less variable than across odontocetes. Although future studies should attempt to use multiple cochleae for every species, our results suggest that using just one cochlea for each species should not strongly influence the conclusions of comparative studies if our results are consistent across Cetacea.

Branislav Kveton, Csaba Szepesvari, Mohammad Ghavamzadeh et al.

We propose a new online algorithm for cumulative regret minimization in a stochastic linear bandit. The algorithm pulls the arm with the highest estimated reward in a linear model trained on its perturbed history. Therefore, we call it perturbed-history exploration in a linear bandit (LinPHE). The perturbed history is a mixture of observed rewards and randomly generated i.i.d. pseudo-rewards. We derive a $\tilde{O}(d \sqrt{n})$ gap-free bound on the $n$-round regret of LinPHE, where $d$ is the number of features. The key steps in our analysis are new concentration and anti-concentration bounds on the weighted sum of Bernoulli random variables. To show the generality of our design, we generalize LinPHE to a logistic model. We evaluate our algorithms empirically and show that they are practical.

Chengcheng Han

A light higgsino is strongly favored by the naturalness, while as a dark matter candidate it is usually under-abundant. We consider the higgsino production in a non-standard history of the universe, caused by a scalar field with an initially displaced vacuum. We find that given a proper reheating temperature induced by the scalar decay, a light higgsino could provide the correct dark matter relic abundance. On the other hand, a sub-TeV higgsino dark matter, once observed, would be a strong hint of the non-standard thermal history of the universe.