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Next-generation sequencing methods provide comprehensive data for the analysis of structural and functional analysis of the genome. The draft genomes with low contig number and high N50 value can give insight into the structure of the genome as well as provide information on the annotation of the genome. In this study, we designed a pipeline that can be used to assemble prokaryotic draft genomes with low number of contigs and high N50 value. We aimed to use combination of two de novo assembly tools (SPAdes and IDBA-Hybrid) and evaluate the impact of this approach on the quality metrics of the assemblies. The followed pipeline was tested with the raw sequence data with short reads (< 300) for a total of 10 species from four different genera. To obtain the final draft genomes, we firstly assembled the sequences using SPAdes to find closely related organism using the extracted 16 s rRNA from it. IDBA-Hybrid assembler was used to obtain the second assembly data using the closely related organism genome. SPAdes assembler tool was implemented using the second assembly, produced by IDBA-hybrid as a hint. The results were evaluated using QUAST and BUSCO. The pipeline was successful for the reduction of the contig numbers and increasing the N50 statistical values in the draft genome assemblies while preserving the coverage of the draft genomes.
Extreme value statistics is a popular and frequently used tool to model the occurrence of large earthquakes. The problem of poor statistics arising from rare events is addressed by taking advantage of the validity of general statistical properties in asymptotic regimes. In this note, I argue that the use of extreme value statistics for the purpose of practically modeling the tail of the frequency-magnitude distribution of earthquakes can produce biased and thus misleading results because it is unknown to what degree the tail of the true distribution is sampled by data. Using synthetic data allows to quantify this bias in detail. The implicit assumption that the true M-max is close to the maximum observed magnitude M-max,M-observed restricts the class of the potential models a priori to those with M-max = M-max,M-observed + Delta M with an increment Delta M approximate to 0.5... 1.2. This corresponds to the simple heuristic method suggested by Wheeler (2009) and labeled :M-max equals M-obs plus an increment." The incomplete consideration of the entire model family for the frequency-magnitude distribution neglects, however, the scenario of a large so far unobserved earthquake.
Models are useful tools for understanding and predicting ecological patterns and processes. Under ongoing climate and biodiversity change, they can greatly facilitate decision-making in conservation and restoration and help designing adequate management strategies for an uncertain future. Here, we review the use of spatially explicit models for decision support and to identify key gaps in current modelling in conservation and restoration. Of 650 reviewed publications, 217 publications had a clear management application and were included in our quantitative analyses. Overall, modelling studies were biased towards static models (79%), towards the species and population level (80%) and towards conservation (rather than restoration) applications (71%). Correlative niche models were the most widely used model type. Dynamic models as well as the gene-to-individual level and the community-to-ecosystem level were underrepresented, and explicit cost optimisation approaches were only used in 10% of the studies. We present a new model typology for selecting models for animal conservation and restoration, characterising model types according to organisational levels, biological processes of interest and desired management applications. This typology will help to more closely link models to management goals. Additionally, future efforts need to overcome important challenges related to data integration, model integration and decision-making. We conclude with five key recommendations, suggesting that wider usage of spatially explicit models for decision support can be achieved by 1) developing a toolbox with multiple, easier-to-use methods, 2) improving calibration and validation of dynamic modelling approaches and 3) developing best-practise guidelines for applying these models. Further, more robust decision-making can be achieved by 4) combining multiple modelling approaches to assess uncertainty, and 5) placing models at the core of adaptive management. These efforts must be accompanied by long-term funding for modelling and monitoring, and improved communication between research and practise to ensure optimal conservation and restoration outcomes.
This paper consists of two parts: In the first part, some of the challenges with which the Internationaal Criminal Court is currently confronted are being presented. First of all, the article will describe the current state of the International Criminal Court and the Rome Statue. Afterwards, the article analyses the Court’s efforts to deal with cases against third-country nationals and the challenges it is facing in that regard. In addition, the Court’s case law will be analyzed in order to determine an increasing ‘emancipation’ of the case law of the International Criminal Court from international humanitarian law. The second part of the paper will briefly discuss the role of domestic international criminal law and domestic courts in the further development and enforcement of international criminal law. As an example of the role that domestic courts may have in clarifying classic issues in international law, the judgment of the German Supreme Court of January 28, 2021 (3 StR 564/19), which deals with the status of costumary international law on functional immunity of State officials before domestic courts, shall be assessed.
Das Völkerstrafrecht steht fast zwanzig Jahre nach dem Inkrafttreten des Römischen Statuts – der völkervertraglichen Grundlage des Internationalen Strafgerichtshofs – angesichts einer inzwischen deutlich veränderten Weltlage an einem Scheideweg. Daher erscheint es geboten, wenn nicht gar zwingend, die Herausforderungen, mit denen sich der Internationale Strafgerichtshof heute konfrontiert sieht, zu analysieren.
Privacy regulations and the physical distribution of heterogeneous data are often primary concerns for the development of deep learning models in a medical context. This paper evaluates the feasibility of differentially private federated learning for chest X-ray classification as a defense against data privacy attacks. To the best of our knowledge, we are the first to directly compare the impact of differentially private training on two different neural network architectures, DenseNet121 and ResNet50. Extending the federated learning environments previously analyzed in terms of privacy, we simulated a heterogeneous and imbalanced federated setting by distributing images from the public CheXpert and Mendeley chest X-ray datasets unevenly among 36 clients. Both non-private baseline models achieved an area under the receiver operating characteristic curve (AUC) of 0.940.94 on the binary classification task of detecting the presence of a medical finding. We demonstrate that both model architectures are vulnerable to privacy violation by applying image reconstruction attacks to local model updates from individual clients. The attack was particularly successful during later training stages. To mitigate the risk of a privacy breach, we integrated Rényi differential privacy with a Gaussian noise mechanism into local model training. We evaluate model performance and attack vulnerability for privacy budgets ε∈{1,3,6,10}�∈{1,3,6,10}. The DenseNet121 achieved the best utility-privacy trade-off with an AUC of 0.940.94 for ε=6�=6. Model performance deteriorated slightly for individual clients compared to the non-private baseline. The ResNet50 only reached an AUC of 0.760.76 in the same privacy setting. Its performance was inferior to that of the DenseNet121 for all considered privacy constraints, suggesting that the DenseNet121 architecture is more robust to differentially private training.
Earthquake site responses or site effects are the modifications of surface geology to seismic waves. How well can we predict the site effects (average over many earthquakes) at individual sites so far? To address this question, we tested and compared the effectiveness of different estimation techniques in predicting the outcrop Fourier site responses separated using the general inversion technique (GIT) from recordings. Techniques being evaluated are (a) the empirical correction to the horizontal-to-vertical spectral ratio of earthquakes (c-HVSR), (b) one-dimensional ground response analysis (GRA), and (c) the square-root-impedance (SRI) method (also called the quarter-wavelength approach). Our results show that c-HVSR can capture significantly more site-specific features in site responses than both GRA and SRI in the aggregate, especially at relatively high frequencies. c-HVSR achieves a "good match" in spectral shape at similar to 80%-90% of 145 testing sites, whereas GRA and SRI fail at most sites. GRA and SRI results have a high level of parametric and/or modeling errors which can be constrained, to some extent, by collecting on-site recordings.
Bimetallic nanostructures comprising plasmonic and catalytic components have recently emerged as a promising approach to generate a new type of photo-enhanced nanoreactors. Most designs however concentrate on plasmon-induced charge separation, leaving photo-generated heat as a side product.
This work presents a photoreactor based on Au-Pd nanorods with an optimized photothermal conversion, which aims to effectively utilize the photo-generated heat to increase the rate of Pd-catalyzed reactions. Dumbbell-shaped Au nanorods were fabricated via a seed-mediated growth method using binary surfactants. Pd clusters were selectively grown at the tips of the Au nanorods, using the zeta potential as a new synthetic parameter to indicate the surfactant remaining on the nanorod surface.
The photothermal conversion of the Au-Pd nanorods was improved with a thin layer of polydopamine (PDA) or TiO2.
As a result, a 60% higher temperature increment of the dispersion compared to that for bare Au rods at the same light intensity and particle density could be achieved.
The catalytic performance of the coated particles was then tested using the reduction of 4-nitrophenol as the model reaction. Under light, the PDA-coated Au-Pd nanorods exhibited an improved catalytic activity, increasing the reaction rate by a factor 3.
An analysis of the activation energy confirmed the photoheating effect to be the dominant mechanism accelerating the reaction. Thus, the increased photothermal heating is responsible for the reaction acceleration.
Interestingly, the same analysis shows a roughly 10% higher reaction rate for particles under illumination compared to under dark heating, possibly implying a crucial role of localized heat gradients at the particle surface.
Finally, the coating thickness was identified as an essential parameter determining the photothermal conversion efficiency and the reaction acceleration.
We present observations of three-dimensional magnetic power spectra in wavevector space to investigate the anisotropy and scalings of sub-Alfvenic solar wind turbulence at magnetohydrodynamic (MHD) scale using the Magnetospheric Multiscale spacecraft. The magnetic power distributions are organized in a new coordinate determined by wavevectors ((kappa) over cap) and background magnetic field ((b) over cap (0)) in Fourier space. This study utilizes two approaches to determine wavevectors: the singular value decomposition method and multispacecraft timing analysis. The combination of the two methods allows an examination of the properties of magnetic field fluctuations in terms of mode compositions without any spatiotemporal hypothesis. Observations show that fluctuations (delta B-perpendicular to 1) in the direction perpendicular to (kappa) over cap and (b) over cap (0) prominently cascade perpendicular to (b) over cap (0), and such anisotropy increases with wavenumbers. The reduced power spectra of 6.8 11 follow Goldreich-Sridhar scalings: (P) over cap (k(perpendicular to)) proportional to k(perpendicular to)(-5/3) and (P) over cap (k(parallel to)) proportional to k(parallel to)(-2). In contrast, fluctuations within the (k) over cap(b) over cap (0) plane show isotropic behaviors: perpendicular power distributions are approximately the same as parallel distributions. The reduced power spectra of fluctuations within the (k) over cap(b) over cap (0) plane follow the scalings (P) over cap (k(perpendicular to)) proportional to k(perpendicular to)(-3/2) and (P) over cap (k(parallel to)) proportional to k(parallel to)(-3/2). Comparing frequency-wavevector spectra with theoretical dispersion relations of MHD modes, we find that delta B-perpendicular to 1 are probably associated with Alfven modes. On the other hand, magnetic field fluctuations within the (k) over cap(b) over cap (0) plane more likely originate from fast modes based on their isotropic behaviors. The observations of anisotropy and scalings of different magnetic field components are consistent with the predictions of current compressible MHD theory. Moreover, for the Alfvenic component, the ratio of cascading time to the wave period is found to be a factor of a few, consistent with critical balance in the strong turbulence regime. These results are valuable for further studies of energy compositions of plasma turbulence and their effects on energetic particle transport.