Fair Inputs and Fair Outputs: The Incompatibility of Fairness in Privacy and Accuracy

Fairness concerns about algorithmic decision-making systems have been mainly focused on the outputs (e.g., the accuracy of a classifier across individuals or groups). However, one may additionally be concerned with fairness in the inputs. In this paper, we propose and formulate two properties regarding the inputs of (features used by) a classifier. In particular, we claim that fair privacy (whether individuals are all asked to reveal the same information) and need-to-know (whether users are only asked for the minimal information required for the task at hand) are desirable properties of a decision system. We explore the interaction between these properties and fairness in the outputs (fair prediction accuracy). We show that for an optimal classifier these three properties are in general incompatible, and we explain what common properties of data make them incompatible. Finally we provide an algorithm to verify if the trade-off between the three properties exists in a given dataset, and use the algorithm to show that this trade-off is common in real data

Courant-like brackets and loop spaces

We study the algebra of local functionals equipped with a Poisson bracket. We discuss the underlying algebraic structures related to a version of the Courant-Dorfman algebra. As a main illustration, we consider the functionals over the cotangent bundle of the superloop space over a smooth manifold. We present a number of examples of the Courant-like brackets arising from this analysis.Comment: 20 pages, the version published in JHE

Chiral de Rham complex on Riemannian manifolds and special holonomy

Interpreting the chiral de Rham complex (CDR) as a formal Hamiltonian quantization of the supersymmetric non-linear sigma model, we suggest a setup for the study of CDR on manifolds with special holonomy. We show how to systematically construct global sections of CDR from differential forms, and investigate the algebra of the sections corresponding to the covariantly constant forms associated with the special holonomy. As a concrete example, we construct two commuting copies of the Odake algebra (an extension of the N=2 superconformal algebra) on the space of global sections of CDR of a Calabi-Yau threefold and conjecture similar results for G_2 manifolds. We also discuss quasi-classical limits of these algebras.Comment: 49 pages, title changed, major rewrite with no changes in the main theorems, published versio

Practical nutritional recovery strategies for elite soccer players when limited time separates repeated matches

Specific guidelines that aim to facilitate the recovery of soccer players from the demands of training and a congested fixture schedule are lacking; especially in relation to evidence-based nutritional recommendations. The importance of repeated high level performance and injury avoidance while addressing the challenges of fixture scheduling, travel to away venues, and training commitments requires a strategic and practically feasible method of implementing specific nutritional strategies. Here we present evidence-based guidelines regarding nutritional recovery strategies within the context of soccer. An emphasis is placed on providing practically applicable guidelines for facilitation of recovery when multiple matches are played within a short period of time (i.e. 48 h). Following match-play, the restoration of liver and muscle glycogen stores (via consumption of ~1.2 gkg-1h-1 of carbohydrate) and augmentation of protein synthesis (via ~40 g of protein) should be prioritised in the first 20 minutes of recovery. Daily intakes of 6-10 gkg-1 body mass of carbohydrate are recommended when limited time separates repeated matches while daily protein intakes of >1.5 gkg-1 body mass should be targeted; possibly in the form of multiple smaller feedings (e.g., 6 x 20-40 g). At least 150% of the body mass lost during exercise should be consumed within 1 h and electrolytes added such that fluid losses are ameliorated. Strategic use of protein, leucine, creatine, polyphenols and omega-3 supplements could also offer practical means of enhancing post-match recovery. Keywords: soccer, nutrition, recovery, polyphenols, omega-3, creatine, fixture, congestio

A Wide Extent of Inter-Strain Diversity in Virulent and Vaccine Strains of Alphaherpesviruses

Alphaherpesviruses are widespread in the human population, and include herpes simplex virus 1 (HSV-1) and 2, and varicella zoster virus (VZV). These viral pathogens cause epithelial lesions, and then infect the nervous system to cause lifelong latency, reactivation, and spread. A related veterinary herpesvirus, pseudorabies (PRV), causes similar disease in livestock that result in significant economic losses. Vaccines developed for VZV and PRV serve as useful models for the development of an HSV-1 vaccine. We present full genome sequence comparisons of the PRV vaccine strain Bartha, and two virulent PRV isolates, Kaplan and Becker. These genome sequences were determined by high-throughput sequencing and assembly, and present new insights into the attenuation of a mammalian alphaherpesvirus vaccine strain. We find many previously unknown coding differences between PRV Bartha and the virulent strains, including changes to the fusion proteins gH and gB, and over forty other viral proteins. Inter-strain variation in PRV protein sequences is much closer to levels previously observed for HSV-1 than for the highly stable VZV proteome. Almost 20% of the PRV genome contains tandem short sequence repeats (SSRs), a class of nucleic acids motifs whose length-variation has been associated with changes in DNA binding site efficiency, transcriptional regulation, and protein interactions. We find SSRs throughout the herpesvirus family, and provide the first global characterization of SSRs in viruses, both within and between strains. We find SSR length variation between different isolates of PRV and HSV-1, which may provide a new mechanism for phenotypic variation between strains. Finally, we detected a small number of polymorphic bases within each plaque-purified PRV strain, and we characterize the effect of passage and plaque-purification on these polymorphisms. These data add to growing evidence that even plaque-purified stocks of stable DNA viruses exhibit limited sequence heterogeneity, which likely seeds future strain evolution

Large expert-curated database for benchmarking document similarity detection in biomedical literature search

Document recommendation systems for locating relevant literature have mostly relied on methods developed a decade ago. This is largely due to the lack of a large offline gold-standard benchmark of relevant documents that cover a variety of research fields such that newly developed literature search techniques can be compared, improved and translated into practice. To overcome this bottleneck, we have established the RElevant LIterature SearcH consortium consisting of more than 1500 scientists from 84 countries, who have collectively annotated the relevance of over 180 000 PubMed-listed articles with regard to their respective seed (input) article/s. The majority of annotations were contributed by highly experienced, original authors of the seed articles. The collected data cover 76% of all unique PubMed Medical Subject Headings descriptors. No systematic biases were observed across different experience levels, research fields or time spent on annotations. More importantly, annotations of the same document pairs contributed by different scientists were highly concordant. We further show that the three representative baseline methods used to generate recommended articles for evaluation (Okapi Best Matching 25, Term Frequency-Inverse Document Frequency and PubMed Related Articles) had similar overall performances. Additionally, we found that these methods each tend to produce distinct collections of recommended articles, suggesting that a hybrid method may be required to completely capture all relevant articles. The established database server located at https://relishdb.ict.griffith.edu.au is freely available for the downloading of annotation data and the blind testing of new methods. We expect that this benchmark will be useful for stimulating the development of new powerful techniques for title and title/abstract-based search engines for relevant articles in biomedical research.Peer reviewe

Exercise Classification with Machine Learning

Innowearable AB has developed a product called Inno-XTM that calculates musclefatigue during three exercises: squat jumps, wall sit, and leg extension. Inno-X uses an accelerometer and a surface electromyography sensor. The goal of thisproject was to create the signal processing part of a machine-learning (ML) pipeline that classifies the exercises in real-time. Data was collected from the sensors to create a training environment that could later be translated to a real-time environment using a sliding window technique. A Savitsky-Golay filter (SG), lowpass, and highpass filters were tested in order to remove noise from the signal. The best filter proved to be the SG filter. Both time and frequency domain features were used in feature extraction. The finished product used 24 features from both domains combined. These methods together with the ML algorithms created in a collabora-tive project led to a classification accuracy for the training environment of 98.62%, while the real-time environment reached 90%. By collecting a larger and more diverse dataset, and addressing the issue of leg extension and wall sit exercises being too similar, real-time classification can be further improved which will make the ML pipeline usable for Innowearables’ customers.Innowearable AB har utvecklat en produkt som heter Inno-XTM som räknar ut muskeltröttheten vid 3  övningar: upphopp, jägarvila och benextensioner. Inno-X använder en accelerometer och en yt-elektromyografi-sensor. Målet med projektet var att skapa signalprocesseringsdelen av en machine learning (ML) pipelinesom klassificerar dessa övningar i realtid. Data samlades in från sensorerna för att skapa en träningsmiljö som sedan kunde gå  över i realtidsmiljö genom attanvända en sliding-window teknik. Savitsky-Golay (SG) filter, högpassfilter, och lågpassfilter användes för att reducera brus i sensorsignalerna. SG filtret presterade bäst. Features från både tids- och frekvensdomän användes i feature extraction. Slutprodukten använde 24 features kombinerat från båda domänen. Dessa metoder tillsammans med ML algoritmer som togs fram i ett partnerprojekt gav ett resultat i träningsmiljön på 98.62% i klassificeringsnoggrannhet och 90% för realtidsmiljön. Genom att samla större mängd data med mer diversitet och lösa problemetatiken i att jägarvila och benextensioner  är för lika, kommer realtidsklas-sifikationen förbättras vilket hade gjort att ML pipelinen blir användbar för Innowearables kunder

Exercise Classification with Machine Learning

Innowearable AB has developed a product called Inno-XTM that calculates musclefatigue during three exercises: squat jumps, wall sit, and leg extension. Inno-X uses an accelerometer and a surface electromyography sensor. The goal of thisproject was to create the signal processing part of a machine-learning (ML) pipeline that classifies the exercises in real-time. Data was collected from the sensors to create a training environment that could later be translated to a real-time environment using a sliding window technique. A Savitsky-Golay filter (SG), lowpass, and highpass filters were tested in order to remove noise from the signal. The best filter proved to be the SG filter. Both time and frequency domain features were used in feature extraction. The finished product used 24 features from both domains combined. These methods together with the ML algorithms created in a collabora-tive project led to a classification accuracy for the training environment of 98.62%, while the real-time environment reached 90%. By collecting a larger and more diverse dataset, and addressing the issue of leg extension and wall sit exercises being too similar, real-time classification can be further improved which will make the ML pipeline usable for Innowearables’ customers.Innowearable AB har utvecklat en produkt som heter Inno-XTM som räknar ut muskeltröttheten vid 3  övningar: upphopp, jägarvila och benextensioner. Inno-X använder en accelerometer och en yt-elektromyografi-sensor. Målet med projektet var att skapa signalprocesseringsdelen av en machine learning (ML) pipelinesom klassificerar dessa övningar i realtid. Data samlades in från sensorerna för att skapa en träningsmiljö som sedan kunde gå  över i realtidsmiljö genom attanvända en sliding-window teknik. Savitsky-Golay (SG) filter, högpassfilter, och lågpassfilter användes för att reducera brus i sensorsignalerna. SG filtret presterade bäst. Features från både tids- och frekvensdomän användes i feature extraction. Slutprodukten använde 24 features kombinerat från båda domänen. Dessa metoder tillsammans med ML algoritmer som togs fram i ett partnerprojekt gav ett resultat i träningsmiljön på 98.62% i klassificeringsnoggrannhet och 90% för realtidsmiljön. Genom att samla större mängd data med mer diversitet och lösa problemetatiken i att jägarvila och benextensioner  är för lika, kommer realtidsklas-sifikationen förbättras vilket hade gjort att ML pipelinen blir användbar för Innowearables kunder

Gå runt i cirklar : Från sigmamodeller till vertexalgebror och tillbaka.

In this thesis, we investigate sigma models and algebraic structures emerging from a Hamiltonian description of their dynamics, both in a classical and in a quantum setup. More specifically, we derive the phase space structures together with the Hamiltonians for the bosonic two-dimensional non-linear sigma model, and also for the N=1 and N=2 supersymmetric models. A convenient framework for describing these structures are Lie conformal algebras and Poisson vertex algebras. We review these concepts, and show that a Lie conformal algebra gives a weak Courant–Dorfman algebra. We further show that a Poisson vertex algebra generated by fields of conformal weight one and zero are in a one-to-one relationship with Courant–Dorfman algebras. Vertex algebras are shown to be appropriate for describing the quantum dynamics of supersymmetric sigma models. We give two definitions of a vertex algebra, and we show that these definitions are equivalent. The second definition is given in terms of a λ-bracket and a normal ordered product, which makes computations straightforward. We also review the manifestly supersymmetric N=1 SUSY vertex algebra. We also construct sheaves of N=1 and N=2 vertex algebras. We are specifically interested in the sheaf of N=1 vertex algebras referred to as the chiral de Rham complex. We argue that this sheaf can be interpreted as a formal quantization of the N=1 supersymmetric non-linear sigma model. We review different algebras of the chiral de Rham complex that one can associate to different manifolds. In particular, we investigate the case when the manifold is a six-dimensional Calabi–Yau manifold. The chiral de Rham complex then carries two commuting copies of the N=2 superconformal algebra with central charge c=9, as well as the Odake algebra, associated to the holomorphic volume form