ShuiEro ... from vague up to sometimes ;) crystal clear drop by drop ...

by Robert Śliwowski, Thierry Paillard, Łukasz Bojkowski, Witold Dudziński, Mikołaj Patek, Jakub Marynowicz

Evaluation of muscle strength imbalance can be an important element in optimizing the training process of soccer players. The purpose of the study was to examine isokinetic peak torque (PT) and total work (TW) exerted by both knee extensors (quadriceps or Q) and flexors (hamstrings or H), intra-limb imbalance and the magnitude and direction of inter-limb asymmetry in top elite senior (n = 109) and junior (n = 74) soccer players. An isokinetic dynamometry was used to measure maximum peak torque of quadriceps (PT-Q) and hamstrings (PT-H) at an angular velocity of 60° ·s-1, as well as the total work for extensors (TW-Q) and flexors (TW-H) at an angular velocity of 240° ·s-1 in the dominant (DL) and non-dominant leg (NDL) during concentric muscle contraction. Intra-limb imbalance and inter-limb asymmetries were calculated using a standard equation. Statistical analysis using t-test and Mann-Whitney U-test revealed: (a) no differences (p > 0.05) between groups for PT-Q and PT-H, (b) greater strength levels (p < 0.05) for TW-Q and TW-H of senior players than juniors, and (c) no differences (p > 0.05) between groups for intra-limb imbalance and inter-limb asymmetry. Additionally, Pearson’s chi-kwadrat (χ2) analysis showed no differences (p > 0.05) between groups for intra-limb imbalance and inter-limb asymmetry in relation to the ’normative’ values accepted in the literature that indicate an increase in the risk of knee injury. This study shows that isokinetic assessment can be an important tool to identify imbalances/asymmetries and to develop strategies to reduce the risk of muscle injury.

by Quoc Bao Diep, Hong Yen Phan, Thanh-Cong Truong

Digital speech recognition is a challenging problem that requires the ability to learn complex signal characteristics such as frequency, pitch, intensity, timbre, and melody, which traditional methods often face issues in recognizing. This article introduces three solutions based on convolutional neural networks (CNN) to solve the problem: 1D-CNN is designed to learn directly from digital data; 2DS-CNN and 2DM-CNN have a more complex architecture, transferring raw waveform into transformed images using Fourier transform to learn essential features. Experimental results on four large data sets, containing 30,000 samples for each, show that the three proposed models achieve superior performance compared to well-known models such as GoogLeNet and AlexNet, with the best accuracy of 95.87%, 99.65%, and 99.76%, respectively. With 5-10% higher performance than other models, the proposed solution has demonstrated the ability to effectively learn features, improve recognition accuracy and speed, and open up the potential for broad applications in virtual assistants, medical recording, and voice commands.

by M. Lukas Seehausen, Alex Rimmer, Abigail Wiesner, Marc Kenis, Cynthia Scott-Dupree, Sandy M. Smith

The box tree moth Cydalima perspectalis (Walker) (Lepidoptera: Crambidae) (BTM) is a native moth throughout eastern Asia, having recently become invasive in Europe (2007) where it feeds on boxwood (= box tree), Buxus spp. The moth rapidly spread across Europe and the Caucasus causing damage to both ornamental and wild Buxus. In 2018, C. perspectalis was found in Toronto, ON, Canada, and has since spread south into the US. To better predict where the moth will establish and have significant impact on ornamental trade in North America, we used most recent scientific literature and distribution points to update the temperature and diapause indices of an existing ecoclimatic CLIMEX model. The model parameters provided a good fit for the potential distribution of BTM compared to its known distribution across eastern Asia and in Europe. Interestingly, our results suggest that the current native distribution in Asia is incomplete and that further expansion is also possible in its introduced range, especially in northern Europe, along the Mediterranean coast of Africa, and eastward to central Russia. In North America, the model predicts that most of North America should be climatically suitable for the moth’s establishment, with the exception of Alaska and the northern territories of Canada, as well as higher elevations in the Rocky Mountains and southern hot and dry areas. Our study highlights the importance of the CLIMEX model to assess the risk of BTM spreading in its newly invaded areas, especially North America, and its use to help make decisions in terms of regulatory dispersal restrictions and choice of management options.

by Caroline Casey, Selene Fregosi, Julie N. Oswald, Vincent M. Janik, Fleur Visser, Brandon Southall

Oceanic delphinids that occur in and around Navy operational areas are regularly exposed to intense military sonar broadcast within the frequency range of their hearing. However, empirically measuring the impact of sonar on the behavior of highly social, free-ranging dolphins is challenging. Additionally, baseline variability or the frequency of vocal state-switching among social oceanic dolphins during undisturbed conditions is lacking, making it difficult to attribute changes in vocal behavior to anthropogenic disturbance. Using a network of drifting acoustic buoys in controlled exposure experiments, we investigated the effects of mid-frequency (3–4 kHz) active sonar (MFAS) on whistle production in short-beaked (Delphinus delphis delphis) and long-beaked common dolphins (Delphinus delphis bairdii) in southern California. Given the complexity of acoustic behavior exhibited by these group-living animals, we conducted our response analysis over varying temporal windows (10 min– 5 s) to describe both longer-term and instantaneous changes in sound production. We found that common dolphins exhibited acute and pronounced changes in whistle rate in the 5 s following exposure to simulated Navy MFAS. This response was sustained throughout sequential MFAS exposures within experiments simulating operational conditions, suggesting that dolphins may not habituate to this disturbance. These results indicate that common dolphins exhibit brief yet clearly detectable acoustic responses to MFAS. They also highlight how variable temporal analysis windows–tuned to key aspects of baseline vocal behavior as well as experimental parameters related to MFAS exposure–enable the detection of behavioral responses. We suggest future work with oceanic delphinids explore baseline vocal rates a-priori and use information on the rate of change in vocal behavior to inform the analysis time window over which behavioral responses are measured.

by Ahmad Ghiasi, Lewis Nkenyereye, Fawwaz Hazzazi, Muhammad Akmal Chaudhary, Maher Assaad, Abbas Rezaei

This research introduces a new designing process and analysis of an innovative Silicon-on-Insulator Metal-Semiconductor Field-Effect (SOI MESFET) structure that demonstrates improved DC and RF characteristics. The design incorporates several modifications to control and reduce the electric field concentration within the channel. These modifications include relocating the transistor channel to sub-regions near the source and drain, adjusting the position of the gate electrode closer to the source, introducing an aluminum layer beneath the channel, and integrating an oxide layer adjacent to the gate. The results show that the AlOx-MESFET configuration exhibits a remarkable increase of 128% in breakdown voltage and 156% in peak power. Furthermore, due to enhanced conductivity and a significant reduction in gate-drain capacitance, there is a notable improvement of 53% in the cut-off frequency and a 28% increase in the maximum oscillation frequency. Additionally, the current gain experiences a boost of 15%. The improved breakdown voltage and peak power make it suitable for applications requiring robust performance under high voltage and power conditions. The increased maximum oscillation frequency and cut-off frequency make it ideal for high-frequency applications where fast signal processing is crucial. Moreover, the enhanced current gain ensures efficient amplification of signals. The introduced SOI MESFET structure with its modifications offers significant improvements in various performance metrics. It provides high oscillation frequency, better breakdown voltage and good cut-off frequency, and current gain compared to the traditional designs. These enhancements make it a highly desirable choice for applications that demand high-frequency and high-power capabilities.

by Samuel A. Matthews, Carlos Coelho, Erick E. Rodriguez Salas, Emma E. Brock, Victoria J. Hodge, James A. Walker, Laurence G. Wilson

The three-dimensional swimming tracks of motile microorganisms can be used to identify their species, which holds promise for the rapid identification of bacterial pathogens. The tracks also provide detailed information on the cells’ responses to external stimuli such as chemical gradients and physical objects. Digital holographic microscopy (DHM) is a well-established, but computationally intensive method for obtaining three-dimensional cell tracks from video microscopy data. We demonstrate that a common neural network (NN) accelerates the analysis of holographic data by an order of magnitude, enabling its use on single-board computers and in real time. We establish a heuristic relationship between the distance of a cell from the focal plane and the size of the bounding box assigned to it by the NN, allowing us to rapidly localise cells in three dimensions as they swim. This technique opens the possibility of providing real-time feedback in experiments, for example by monitoring and adapting the supply of nutrients to a microbial bioreactor in response to changes in the swimming phenotype of microbes, or for rapid identification of bacterial pathogens in drinking water or clinical samples.

by Mio Uneme, Kazuya Ishikawa, Kazuyuki Furuta, Atsuko Yamashita, Chikara Kaito

The flagellar motor proteins, MotA and MotB, form a complex that rotates the flagella by utilizing the proton motive force (PMF) at the bacterial cell membrane. Although PMF affects the susceptibility to aminoglycosides, the effect of flagellar motor proteins on the susceptibility to aminoglycosides has not been investigated. Here, we found that MotB overexpression increased susceptibility to aminoglycosides, such as kanamycin and gentamicin, in Bacillus subtilis without affecting swimming motility. MotB overexpression did not affect susceptibility to ribosome-targeting antibiotics other than aminoglycosides, cell wall-targeting antibiotics, DNA synthesis-inhibiting antibiotics, or antibiotics inhibiting RNA synthesis. Meanwhile, MotB overexpression increased the susceptibility to aminoglycosides even in the motA-deletion mutant, which lacks swimming motility. Overexpression of the MotB mutant protein carrying an amino acid substitution at the proton-binding site (D24A) resulted in the loss of the enhanced aminoglycoside-sensitive phenotype. These results suggested that MotB overexpression sensitizes B. subtilis to aminoglycosides in a motility-independent manner. Notably, the aminoglycoside-sensitive phenotype induced by MotB requires the proton-binding site but not the MotA/MotB complex formation.

by Md. Mamunur Roshid, M. M. Rahman, Harun-Or Roshid, Md. Habibul Bashar

This work explores diverse novel soliton solutions of two fractional nonlinear models, namely the truncated time M-fractional Chafee-Infante (tM-fCI) and truncated time M-fractional Landau-Ginzburg-Higgs (tM-fLGH) models. The several soliton waves of time M-fractional Chafee-Infante model describe the stability of waves in a dispersive fashion, homogeneous medium and gas diffusion, and the solitary waves of time M-fractional Landau-Ginzburg-Higgs model are used to characterize the drift cyclotron movement for coherent ion-cyclotrons in a geometrically chaotic plasma. A confirmed unified technique exploits soliton solutions of considered fractional models. Under the conditions of the constraint, fruitful solutions are gained and verified with the use of the symbolic software Maple 18. Keeping special values of the constraint, this inquisition achieved kink shape, the collision of kink type and lump wave, the collision of lump and bell type, periodic lump wave, bell shape, some periodic soliton waves for time M-fractional Chafee-Infante and periodic lump, and some diverse periodic and solitary waves for time M-fractional Landau-Ginzburg-Higgs model successfully. The required solutions in this work have many constructive descriptions, and corporal behaviors have been incorporated through some abundant 3D figures with density plots. We compare the m-fractional derivative with the beta fractional derivative and the classical form of these models in two-dimensional plots. Comparisons with others’ results are given likewise.

by Longyan Ran, Yunhe Cui, Jianpeng Zhao, Hongzhen Yang

The decoupling of control and forwarding layers brings Software-Defined Networking (SDN) the network programmability and global control capability, but it also poses SDN security risks. The adversaries can use the forwarding and control decoupling character of SDN to forge legitimate traffic, launching saturation attacks targeted at SDN switches. These attacks can cause the overflow of switch flow tables, thus making the switch cannot forward benign network traffic. How to effectively detect saturation attack is a research hotspot. There are only a few graph-based saturation attack detection methods. Meanwhile, the current graph generation methods may take useless or misleading information to the attack detection, thus decreasing the attack detection accuracy. To solve the above problems, this paper proposes TITAN, a bidirecTional forwardIng graph-based saturaTion Attack detectioN method. TITAN defines flow forwarding rules and topology information, and designs flow statistical features. Based on these definitions, TITAN generates nodes of the bi-forwarding graph based on the flow statistics features and edges of the bi-forwarding graph based on the network traffic routing paths. In this way, each traffic flow in the network is transformed into a bi-directional forwarding graph. Then TITAN feeds the above bidirectional forwarding graph into a Graph Convolutional Network (GCN) to detect whether the flow is a saturation attack flow. The experimental results show that TITAN can effectively detect saturation attacks in SDNs with a detection accuracy of more than 97%.

by Yang Liu, Mei-Po Kwan

Advanced nighttime light (NTL) remote sensing techniques enable the large-scope epidemiological investigations of people’s exposure to outdoor artificial light at night (ALAN) and its health effects. However, multiple uncertainties remain in the measurements of people’s exposure to outdoor ALAN, including the representations of outdoor ALAN, the contextual settings of exposure measurements, and measurement approaches. Non-exposed but included outdoor ALAN and causally irrelevant outdoor ALAN may manifest as contextual errors, and these uncertain contextual errors may lead to biased measurements and erroneous interpretations when modeling people’s health outcomes. In this study, we systematically investigated outdoor ALAN exposure measurements in different geographic contexts using either residence-based or mobility-oriented measurements, different spatial scales, and multiple NTL data sources. Based on the GPS data collected from 208 participants in Hong Kong, outdoor ALAN exposures were measured from NTL imagery at 10 m, 130 m, and 500 m spatial resolutions using in-situ methods or 100 m, 300 m, and 500 m buffer zone averaging. Descriptive analysis, multiple t-tests, and logistic regression were employed to examine the differences between outdoor ALAN exposure measurements using various contextual settings and their effects on modeling people’s overall health. Our results confirmed that different contextual settings may lead to significantly different outdoor ALAN exposure measurements. Our results also confirmed that contextual errors may lead to erroneous conclusions when using improper contextual settings to model people’s overall health. Consequentially, we suggest measuring people’s exposure to outdoor ALAN using the mobility-oriented approach, NTL representation with the high spatial resolution, and a very small buffer zone as a contextual unit to derive outdoor ALAN exposure. This study articulates essential methodological issues induced by uncertainties in outdoor ALAN exposure measurements and can provide essential implications and suggestions for a broad scope of studies that need accurate outdoor ALAN exposure measurements.

by Qing Guo, Xiaojia Lu, Tao Liu, Mengtao Yang, Kai Wang, Yande Zhao, Liang Tao

Aqueous phase trapping (APT), which is one of the most prominent damages, seriously restricts the natural gas production in tight gas sandstone with low permeability. Pore size and microscopic pore structures are the most important factors to determine the water blocking damage. In this paper, 9 core samples from tight gas sandstone with various physical properties were employed, and the pore size distribution (PSD) of the core samples were investigated by high pressure mercury intrusion tests (HPMI). Results showed that the porosity of core samples ranges from 5.68% to 13.7%, and the permeability ranges from 0.00456 to 7.86 mD, which is a typical tight reservoir with strong heterogeneity. According to the HPMI capillary curve, the cores can be divided into two types: Type I and Type II, and the pore sizes of type I are larger than that of type II. Fractal distributions were obtained using HPMI data to further determine the pore structure characteristics of tight reservoirs. The pore structures of tight sandstones display the multifractal fractal feature: D1 corresponding to macro-pores, and D2 corresponding to fractal dimension of micro-pores. Furthermore, APT damage was determined by the permeability recovery ratios (Kr) after gas flooding tests. The correlation of Kr and PSD and fractal dimensions were jointly analyzed in tight gas sandstone. Although positive correlations between pore size parameters and the permeability recovery ratios were observed with relatively weak correlations, for those core samples with very close permeability, pore size parameters (both permeability and PSD) is inadequate in clarifying this damage. The fractal dimension can well describe the complexity and heterogeneity of flow channels in pores, which can become the determining factor to distinguish the flow capacity of tight sandstone. The D2 for samples of type I and type II exhibited a good negative relation with Kr with a correlation coefficient of 0.9878 and 0.7723, respectively. The significance of this finding is that for tight gas sandstone, fractal dimensions, especially the small pore fractal dimension (D2), can be used to predict the possible APT damage very well.

by Pi Yuan, Chen Li, Peng Tang, Bin Yuan, Yongjing Yin

Empty large volume parenteral (LVP) bottle has irregular shape and narrow opening, and its detection accuracy of the foreign substances at the bottom is higher than that of ordinary packaging bottles. The current traditional detection method for the bottom of LVP bottles is to directly use manual visual inspection, which involves high labor intensity and is prone to visual fatigue and quality fluctuations, resulting in limited applicability for the detection of the bottom of LVP bottles. A geometric constraint-based detection model (GCBDM) has been proposed, which combines the imaging model and the shape characteristics of the bottle to construct a constraint model of the imaging parameters, according to the detection accuracy and the field of view. Then, the imaging model is designed and optimized for the detection. Further, the generalized GCBDM has been adopted to different bottle bottom detection scenarios, such as cough syrup and capsule medicine bottles by changing the target parameters of the model. The GCBDM, on the one hand, can avoid the information at the bottom being blocked by the narrow opening in the imaging optical path. On the other hand, by calculating the maximum position deviation between the center of visual inspection and the center of the bottom, it can provide the basis for the accuracy design of the transmission mechanism in the inspection, thus further ensuring the stability of the detection.

by Youngjune Bhak, Albert Tenesa

Aims

Association between whole blood viscosity (WBV) and an increased risk of cardiovascular disease (CVD) has been reported. However, the causal relationship between WBV and CVD remains not thoroughly investigated. The aim of this study was to investigate the causal relation between WBV and CVD.

Methods

Two-sample Mendelian randomization (MR) was employed, with inverse variance weighting (IVW) as the primary method, to investigate the casual relationship between WBV and CVD. The calculated WBV and medical records of 378,210 individuals participating in the UK Biobank study were divided into halves and analyzed.

Results

The means of calculated WBVs were 16.9 (standard deviation: 0.8) and 55.1 (standard deviation: 17.2) for high shear rate (HSR) and low shear rate (LSR), respectively. 37,859 (10.0%) major cardiovascular events (MACE) consisted of 23,894 (6.3%) cases of myocardial infarction (MI), 9,245 (2.4%) cases of ischemic stroke, 10,377 (2.7%) cases of revascularization, and 5,703 (1.5%) cases of coronary heart disease-related death. In the MR analysis, no evidence was found indicating a causal effect of WBV on MACE (IVW p-value for HSR = 0.81, IVW p-value for LSR = 0.47), MI (0.92, 0.83), ischemic stroke (0.52, 0.74), revascularization (0.71, 0.54), and coronary heart disease-related death (0.83, 0.70). The lack of sufficient evidence for causality persisted in other MR methods, including weighted median and MR-egger.

Conclusions

The Mendelian randomization analysis conducted in this study does not support a causal relationship between calculated WBV and CVD.

by Rui Meng, Kristofer E. Bouchard

The brain produces diverse functions, from perceiving sounds to producing arm reaches, through the collective activity of populations of many neurons. Determining if and how the features of these exogenous variables (e.g., sound frequency, reach angle) are reflected in population neural activity is important for understanding how the brain operates. Often, high-dimensional neural population activity is confined to low-dimensional latent spaces. However, many current methods fail to extract latent spaces that are clearly structured by exogenous variables. This has contributed to a debate about whether or not brains should be thought of as dynamical systems or representational systems. Here, we developed a new latent process Bayesian regression framework, the orthogonal stochastic linear mixing model (OSLMM) which introduces an orthogonality constraint amongst time-varying mixture coefficients, and provide Markov chain Monte Carlo inference procedures. We demonstrate superior performance of OSLMM on latent trajectory recovery in synthetic experiments and show superior computational efficiency and prediction performance on several real-world benchmark data sets. We primarily focus on demonstrating the utility of OSLMM in two neural data sets: μECoG recordings from rat auditory cortex during presentation of pure tones and multi-single unit recordings form monkey motor cortex during complex arm reaching. We show that OSLMM achieves superior or comparable predictive accuracy of neural data and decoding of external variables (e.g., reach velocity). Most importantly, in both experimental contexts, we demonstrate that OSLMM latent trajectories directly reflect features of the sounds and reaches, demonstrating that neural dynamics are structured by neural representations. Together, these results demonstrate that OSLMM will be useful for the analysis of diverse, large-scale biological time-series datasets.

Die Fakultät für Informatik der Universität Wien feiert heuer ihr 20-jähriges Bestehen und 50 Jahre Lehrprogramm im Bereich Informatik an der Universität Wien. Aus diesem Grund laden die Fakultät für Informatik und der Forschungsverbund Data Science @ Uni Vienna am 7. Mai 2024 als ersten Programmpunkt des Jubiläumsjahrs zu einem Vortrag des weltweit anerkannten Informatikers Yoshua Bengio ein. Der Turing Award Gewinner wird als einer der "Godfathers of AI" bezeichnet und setzt sich für eine verantwortungsvolle Entwicklung von KI-Techniken ein. In seinem Vortrag in englischer Sprache mit dem Titel "Obtaining Safety Guarantees to avoid AI Catastrophic Risks" wird der Universitätsprofessor der Université de Montreal zunächst den Kontext von Katastrophenszenarien künftiger fortgeschrittener KI-Systeme erläutern, sowohl in Hinblick auf gefährlichen Missbrauch (Bedrohung der Demokratie und der nationalen Sicherheit) als auch auf den Verlust der Kontrolle an übermenschliche KI-Systeme. Dadurch wird deutlich, dass sowohl die technische Herausforderung der Ausrichtung als auch die politische Herausforderung der Koordination und Governance auf nationaler und internationaler Ebene gemeistert werden muss.  Insbesondere wird er den Vorschlag eines multilateralen Netzwerks von öffentlich finanzierten, gemeinnützigen KI-Labors erörtern, die sich auf das mögliche Auftauchen von abtrünnigen KI-Systemen vorbereiten. Abschließend wird Bengio ein Forschungsprogramm zum maschinellen Lernen skizzieren, um quantitative und konservative Risikobewertungen zur Bewältigung der Ausrichtungsherausforderungen zu erhalten.  Über Yoshua Bengio Yoshua Bengio ist Universitätsprofessor im Department of Computer Science and Operations Research an der Université de Montreal, Gründer und wissenschaftlicher Leiter von Mila sowie wissenschaftlicher Leiter des Forschungskonsortiums IVADO. Er gilt als einer der weltweit führenden Köpfe auf dem Gebiet der künstlichen Intelligenz und des Deep Learning und wurde 2018 zusammen mit Geoffrey Hinton und Yann LeCun mit dem A.M. Turing Award, dem "Nobelpreis für Informatik", ausgezeichnet. Bengio ist Fellow der Royal Society of London und Kanadas, Offizier des Order of Canada, Ritter der französischen Ehrenlegion und Mitglied des wissenschaftlichen Beirats der Vereinten Nationen für unabhängige Beratung über Durchbrüche in Wissenschaft und Technologie. Mehr Informationen finden Sie hier.  Vortrag mit Yoshua Bengio "Obtaining Safety Guarantees to avoid AI Catastrophic Risks" Zeit: Dienstag, 7. Mai 2024, 17.00 Uhr
Ort: BIG-Hörsaal, Universitätsring 1, 1010 Wien Der Eintritt zur Veranstaltung ist frei, eine Anmeldung ist erforderlich Der Vortrag wird auch gestreamt. Jubiläum der Fakultät für Informatik

An der Fakultät für Informatik werden im Jahr 2024 gleich zwei Jubiläen gefeiert: Einerseits besteht eine eigenständige Informatik-Fakultät an der Unviersität Wien seit 20 Jahren, andererseits wurde vor 50 Jahren ein kanonisiertes Lehrprogramm im Bereich Informatik an der Universität Wien etabliert. Im Jahr 2024 sind daher einige Veranstaltungen geplant. Eine Übersicht über diese finden Sie hier: https://informatik.univie.ac.at/jubilaeum/

Fakultät für Informatik der Universität Wien Die Fakultät für Informatik der Universität Wien versteht sich als innovative und zukunftsorientierte Fakultät im Lehr- und Forschungsverband der traditionsreichen Universität Wien. Ausgehend von einem starken fachlichen Kern eröffnen die fachliche Vielfalt und das breite Fächerspektrum der Universität Wien viele Möglichkeiten für eine moderne Informatik, die zunehmend Anwendungsgebiete an den Schnittstellen zu Naturwissenschaften, Wirtschaftswissenschaften, Medizin sowie Sozial- und Geisteswissenschaften erschließt. Weitere Informationen 

Forschungsverbund Data Science @ Uni Vienna Der Forschungsverbund wurde 2018 gegründet und hat derzeit 31 Mitglieder aus elf Fakultäten der Universität Wien. Das Ziel ist, verschiedene Forscher*innen der Universität Wien zusammen zu bringen und Data Science in seiner technischen Tiefe und auch seinen Auswirkungen in Gesellschaft und Wissenschaft zu erforschen. Neben dem jährlichen Data Science Day dient eine wissenschaftliche Vortragsreihe dem intellektuellen Austausch zu allen Themen im Bereich Data Science. Weitere Informationen hier. Semesterfrage 2024: Wissen wir, was KI wissen wird? Künstliche Intelligenz ist dabei, unsere Vorstellung von Wissen und Lernen, von Wissensproduktion und Wissensvermittlung radikal zu verändern. Erschüttert KI die Grundfesten unseres Wissens, befeuert Fake News, Verschwörungsmythen und die Krise der Demokratie? Oder stehen wir am Beginn eines goldenen Zeitalters des Wissens mit neuen Chancen, die akuten Probleme der Zeit zu lösen? Expert*innen der Uni Wien diskutieren aktuell ein Semester lang, wie unsere Gesellschaft von der neuen Technologie profitieren kann und warum Wissenschaft und Bildung dabei eine zentrale Rolle spielen. www.rudolphina.univie.ac.at/ki-wissen Abbildung:  Abb. 1: C: Yoshua Bengio

Cichlid fishes exhibit differing degrees of curiosity. The cause for this lies in their genes, as reported by researchers from the University of Basel in the journal Science. This trait influences the cichlids' ability to adapt to new habitats.

In a landmark study based on one of the most comprehensive genomic datasets ever assembled, a team led by scientists at the University of Wisconsin–Madison and Vanderbilt University offer a possible answer to one of the oldest questions about evolution: why some species are generalists and others specialists.

Competition and cooperation are fundamental forces that govern the evolutionary and ecological dynamics among species. The balance between these forces varies across ecological contexts, with some environments favoring cooperative behaviors that promote mutual benefit, while others reward competitive strategies that maximize individual fitness.

by Ruihong Wang, Zexin Jing, Hao Luo, Shun Bao, Jingru Jia, Xiaoyu Zhan

Natural disasters such as landslides often occur on soil slopes in seasonally frozen areas that undergo freeze‒thaw cycling. Ecological slope protection is an effective way to prevent such disasters. To explore the change in the mechanical properties of soil under the influence of both root reinforcement and freeze‒thaw cycles and its influence on slope stability, the Baijiabao landslide in the Three Gorges Reservoir area was taken as an example. The mechanical properties of soil under different confining pressures, vegetation coverages (VCs) and numbers of freeze‒thaw cycles were studied via mechanical tests, such as triaxial compression tests, wave velocity tests and FLAC3D simulations. The results show that the shear strength of a root–soil composite increases with increasing confining pressure and VC and decreases with increasing number of freeze‒thaw cycles. Bermuda grass roots and confining pressure jointly improve the durability of soil under freeze‒thaw conditions. However, with an increase in the number of freeze‒thaw cycles, the resistance of root reinforcement to freeze‒thaw action gradually decreases. The observed effect of freeze‒thaw cycles on soil degradation was divided into three stages: a significant decrease in strength, a slight decrease in strength and strength stability. Freeze‒thaw cycles and VC mainly affect the cohesion of the soil and have little effect on the internal friction angle. Compared with that of a bare soil slope, the safety factor of a slope covered with plants is larger, the maximum displacement of a landslide is smaller, and it is less affected by freezing and thawing. These findings can provide a reference for research on ecological slope protection technology.

by Dominik Fahrner, Ginny Catania, Michael G. Shahin, Dougal D. Hansen, Karina Löffler, Jakob Abermann

Greenland’s glaciers have been retreating, thinning and accelerating since the mid-1990s, with the mass loss from the Greenland Ice Sheet (GrIS) now being the largest contributor to global sea level rise. Monitoring changes in glacier dynamics using in-situ or remote sensing methods has been and remains therefore crucial to improve our understanding of glaciological processes and the response of glaciers to changes in climate. Over the past two decades, significant advances in technology have provided improvements in the way we observe glacier behavior and have helped to reduce uncertainties in future projections. This review focuses on advances in in-situ monitoring of glaciological processes, but also discusses novel methods in satellite remote sensing. We further highlight gaps in observing, measuring and monitoring glaciers in Greenland, which should be addressed in order to improve our understanding of glacier dynamics and to reduce in uncertainties in future sea level rise projections. In addition, we review coordination and inclusivity of science conducted in Greenland and provide suggestion that could foster increased collaboration and co-production.