Polar Cremona Transformations and Monodromy of Polynomials

Consider the gradient map associated to any non-constant homogeneous polynomial f\in \C[x_0,...,x_n] of degree $d$, defined by \phi_f=grad(f): D(f)\to \CP^n, (x_0:...:x_n)\to (f_0(x):...:f_n(x)) where D(f)=\{x\in \CP^n; f(x)\neq 0\} is the principal open set associated to $f$ and $f_i=\frac{\partial f}{\partial x_i}$. This map corresponds to polar Cremona transformations. In Proposition \ref{p1} we give a new lower bound for the degree $d(f)$ of $\phi_f$ under the assumption that the projective hypersurface $V:f=0$ has only isolated singularities. When $d(f)=1$, Theorem \ref{t4} yields very strong conditions on the singularities of $V$.Comment: 8 page

Side-channel based intrusion detection for industrial control systems

Industrial Control Systems are under increased scrutiny. Their security is historically sub-par, and although measures are being taken by the manufacturers to remedy this, the large installed base of legacy systems cannot easily be updated with state-of-the-art security measures. We propose a system that uses electromagnetic side-channel measurements to detect behavioural changes of the software running on industrial control systems. To demonstrate the feasibility of this method, we show it is possible to profile and distinguish between even small changes in programs on Siemens S7-317 PLCs, using methods from cryptographic side-channel analysis.Comment: 12 pages, 7 figures. For associated code, see https://polvanaubel.com/research/em-ics/code

Is surgery the only option for unstable ankle fracture?

Background: Ankle fracture is one of the most common injuries in sports and daily activity. Unstable ankle fracture that are displaced fracture of the lateral malleolus and most bimalleolar or trimalleolar fractures need surgical reduction and fixation.Methods: It is a single centre study in which all unstable ankle fracture above the age of 18 and not associated with any other injury were included in the study. Following fixation patients were followed up at 6 weeks, 3 months and 6 months and functional outcome was assessed with American Orthopaedic Foot and Ankle score (AOFAS).Results: Supination external rotation injury was most common type. Mean AOFAS score at the end of six months was found to be best in supination adduction type. Posterior malleolus fixation with screw were found to have maximum AOFAS score.Conclusions: Surgical outcome in unstable ankle fracture are proved to have good functional outcome

Chapare mammarenavirus - a new deadly virus outbreak: a review

In 2003 an emerging mammarenavirus (formerly arenaviruses) was discovered in Bolivia and named Chapare (CHAPV). It was related to severe and fatal haemorrhagic fever, being similar in clinical features to Machupo (MACV). In mid-2019, CHAPV was the explanation for a cluster of 5 cases, two of them laboratory confirmed, three of them fatal. Reverse transcription polymerase chain reaction (RT-PCR) analysis and subsequent analysis of the entire virus S and L ribonucleic acid (RNA) segment sequences identified the virus as a member of the New World Clade B arenaviruses, which includes all the pathogenic South American arenaviruses. The virus was shown to be most closely associated with Sabia´ virus, but with 26% and 30% nucleotide difference within the S and L segments, and 26%, 28%, 15% and 22% aminoalkanoic acid differences for the L, Z, N, and GP proteins. LUJV, CHAPV, GTOV, and SABV, which are geographically restricted, have been associated with only a few to a few dozen cases. They are, therefore, relatively unimportant to clinicians compared to many other viruses that are usually co-endemic. However, MACV, JUNV, and especially LASV have caused large outbreaks (LASV has caused hundreds of thousands of infections per year). Visitors to countries in which these viruses are endemic, or war-fighters that are deployed to these countries, need to be aware of how to prevent and suspect a mammarenavirus infection

Back to Massey: Impressively fast, scalable and tight security evaluation tools

None of the existing rank estimation algorithms can scale to large cryptographic keys, such as 4096-bit (512 bytes) RSA keys. In this paper, we present the first solution to estimate the guessing entropy of arbitrarily large keys, based on mathematical bounds, resulting in the fastest and most scalable security evaluation tool to date. Our bounds can be computed within a fraction of a second, with no memory overhead, and provide a margin of only a few bits for a full 128-bit AES key

Computing the everyday: social media as data platforms

We conceive social media platforms as sociotechnical entities that variously shape user platform involvement and participation. Such shaping develops along three fundamental data operations that we subsume under the terms of encoding, aggregation, and computation. Encoding entails the engineering of user platform participation along narrow and standardized activity types (e.g., tagging, liking, sharing, following). This heavily scripted platform participation serves as the basis for the procurement of discrete and calculable data tokens that are possible to aggregate and, subsequently, compute in a variety of ways. We expose these operations by investigating a social media platform for shopping. We contribute to the current debate on social media and digital platforms by describing social media as posttransactional spaces that are predominantly concerned with charting and profiling the online predispositions, habits, and opinions of their user base. Such an orientation sets social media platforms apart from other forms of mediating online interaction. In social media, we claim, platform participation is driven toward an endless online conversation that delivers the data footprint through which a computed sociality is made the source of value creation and monetization

Computational Fluid Dynamics of Catalytic Reactors

Today, the challenge in chemical and material synthesis is not only the development of new catalysts and supports to synthesize a desired product, but also the understanding of the interaction of the catalyst with the surrounding flow field. Computational Fluid Dynamics or CFD is the analysis of fluid flow, heat and mass transfer and chemical reactions by means of computer-based numerical simulations. CFD has matured into a powerful tool with a wide range of applications in industry and academia. From a reaction engineering perspective, main advantages are reduction of time and costs for reactor design and optimization, and the ability to study systems where experiments can hardly be performed, e.g., hazardous conditions or beyond normal operation limits. However, the simulation results will always remain a reflection of the uncertainty in the underlying models and physicochemical parameters so that in general a careful experimental validation is required. This chapter introduces the application of CFD simulations in heterogeneous catalysis. Catalytic reactors can be classified by the geometrical design of the catalyst material (e.g. monoliths, particles, pellets, washcoats). Approaches for modeling and numerical simulation of the various catalyst types are presented. Focus is put on the principal concepts for coupling the physical and chemical processes on different levels of details, and on illustrative applications. Models for surface reaction kinetics and turbulence are described and an overview on available numerical methods and computational tools is provided

LDA-Based Clustering as a Side-Channel Distinguisher

Side-channel attacks put the security of the implementations of cryptographic algorithms under threat. Secret information can be recovered by analyzing the physical measurements acquired during the computations and using key recovery distinguishing functions to guess the best candidate. Several generic and model based distinguishers have been proposed in the literature. In this work we describe two contributions that lead to better performance of side-channel attacks in challenging scenarios. First, we describe how to transform the physical leakage traces into a new space where the noise reduction is near-optimal. Second, we propose a new generic distinguisher that is based upon minimal assumptions. It approaches a key distinguishing task as a problem of classification and ranks the key candidates according to the separation among the leakage traces. We also provide experiments and compare their results to those of the Correlation Power Analysis (CPA). Our results show that the proposed method can indeed reach better success rates even in the presence of significant amount of noise