nils-herrmann/clean_scirepeval huggingface dataset:
Bootstrapping EEG based auditory attention detection systems: boundary conditions for background noise and speaker positions
Year: 2018

A listener's neural responses can be decoded to identify the speaker the person is attending to in a cocktail party environment. Such auditory attention detection methods have the potential to provide noise suppression algorithms in hearing devices with information about the listener's attention. A challenge is the effect of noise and other acoustic conditions that can reduce the attention detection accuracy. Specifically, noise can impact the ability of the person to segregate the sound sources and perform selective attention, as well as the external signal processing necessary to decode the attention effectively. The aim of this work is to systematically analyze the effect of noise level and speaker position on attention decoding accuracy.  28 subjects participated in the experiment. Auditory stimuli consisted of stories narrated by different speakers from 2 different locations, along with surrounding multi talker background babble. EEG signals of the subjects were recorded while they focused on one story and ignored the other. The strength of the babble noise as well as the spatial separation between the two speakers were varied between presentations. Spatio temporal decoders were trained for each subject, and applied to decode attention of the subjects from every 30s segment of data. Behavioral speech recognition thresholds were obtained for the different speaker separations.  Both the background noise level and the angular separation between speakers affected attention decoding accuracy. Remarkably, performance was seen to increase with the inclusion of moderate background noise (versus no noise) while across the different noise conditions performance dropped significantly with increasing noise level. We also observed that decoding accuracy improved with increasing speaker separation, exhibiting the advantage of spatial release from masking. Furthermore, the effect of speaker separation on the decoding accuracy became stronger when the background noise level increased. A significant correlation between speech intelligibility and attention decoding accuracy was found across conditions.  This work shows how the background noise level and relative positions of competing talkers impact attention decoding accuracy. It indicates in which circumstances a neuro steered noise suppression system may need to operate, in function of acoustic conditions. It also indicates the boundary conditions for bootstrapping EEG based attention detection systems in neuro steered hearing prostheses.
Applications of AI in cybersecurity
Venue: 2020 Second International Conference on Transdisciplinary AI (TransAI)
Year: 2020

Issues related to digital security are, there is no doubt for this, of utmost importance in the development of methods and support measures for organisations to successfully prepare for as well as realise their digital transformation. While big organisations and businesses may afford to buy services or develop their own in house know how and tools, small and medium sized businesses are not having the means for this, be them financial resources, human resources or technology itself. This dystopic situation may on the other hand offer an unexpected and as of today yet unprecedented chance for innovations in terms of bridging the gap and addressing the need with use of AI technologies and services. In the paper we elaborate on a scenario that we have been developing as part of a European project that is part of the European Horizons 2020 project CS AWARE.
EpCAM independent isolation of circulating tumor cells with epithelial to mesenchymal transition and cancer stem cell phenotypes using ApoStream(r) in patients with breast cancer treated with primary systemic therapy
Venue: PloS one
Year: 2020

Tumor cells with a mesenchymal phenotype and/or cancer stem like cells (CSCs) are known to contribute to metastasis and drug resistance. Circulating tumor cells (CTCs) undergoing epithelial mesenchymal transition (EMT) and CTCs reflecting a dedifferentiated CSC phenotype may not be detected using only an anti EpCAM antibody to capture them. We used an antibody independent CTC enrichment platform, ApoStream(r) which does not rely on any antibody, including anti EpCAM, to capture EMT and CSC CTCs in breast cancer patients who received neoadjuvant chemotherapy and correlated them to pathological complete response (pCR) Methods Blood samples from newly diagnosed breast cancer patients were prospectively collected before neoadjuvant chemotherapy (T0) after chemotherapy but before surgery (T1) and after surgery (T2) and processed using ApoStream. CTCs detected were stained with additional markers to define 3 CTC subsets with the following phenotypes: epithelial CTCs (CK+ EpCAM+ or E cadherin+ EMT CTCs (b catenin+ or vimentin+ and CSC CTCs (CD44+ and CD24low)  We enrolled 55 patients, 47 of which had data for analysis. EMT CTCs were detected in 57% 62% and 72% and CSC CTCs in 9% 22% and 19% at the T0, T1, and T2 time points, respectively. Counts of epithelial (P 0.225) and EMT (P 0.522) phenotypes of CTCs at T0 did not significantly predict pCR. Moreover, no correlation between CTC count change and pCR was demonstrated.  ApoStream was successful in detecting EMT CTCs among patients after neoadjuvant chemotherapy. However, EMT /CSC CTC counts did not correlate with pCR. Due to the small sample size and heterogeneity of this patient population, further study in a larger cohort of molecularly homogeneous patients is warranted.
Face Anti Spoofing via Adversarial Cross Modality Translation
Venue: IEEE Transactions on Information Forensics and Security
Year: 2021

Face Presentation Attack Detection (PAD) approaches based on multi modal data have been attracted increasingly by the research community. However, they require multi modal face data consistently involved in both the training and testing phases. It would severely limit the applicability due to the most Face Anti spoofing (FAS) systems are only equipped with Visible (VIS) imaging devices, i.e. RGB cameras. Therefore, how to use other modality (i.e. Near Infrared (NIR) to assist the performance improvement of VIS based PAD is significant for FAS. In this work, we first discuss the big gap of performances among different modalities even though the same backbone network is applied. Then, we propose a novel Cross modal Auxiliary (CMA) framework for the VIS based FAS task. The main trait of CMA is that the performance can be greatly improved with the help of other modality while no other modality is required in the testing stage. The proposed CMA consists of a Modality Translation Network (MT Net) and a Modality Assistance Network (MA Net) The former aims to close the visible gap between different modalities via a generative model that maps inputs from one modality (i.e. RGB) to another (i.e. NIR) The latter focuses on how to use the translated modality (i.e. target modality) and RGB modality (i.e. source modality) together to train a discriminative PAD model. Extensive experiments are conducted to demonstrate that the proposed framework can push the state of the art (SOTA) performances on both multi modal datasets (i.e. CASIA SURF, CeFA, and WMCA) and RGB based datasets (i.e. OULU NPU, and SiW)
A Ka Band Power Amplifier with Reconfigurable Impedance Matching Network
Venue: 2019 IEEE 19th Topical Meeting on Silicon Monolithic Integrated Circuits in RF Systems (SiRF)
Year: 2019

A tunable matching network integrated with the power amplifier (PA) is described that can adapt to potential impedance variations presented by the antenna. The matching network is designed to match loads within half gamma around nominal 50 \Omega$ impedance. The tunability is achieved by modifying the length of transmission line segments within the matching network by using reverse saturated SiGe switches. S parameters and load pull measurements have been obtained and demonstrate that the PA is able to adapt to different load impedances, therefore is able provide constant PAE and output power at a significantly extended range of impedance variations. In this paper, the design approach is explained that leads to significantly improved performance of the presented PA compared to previously published reconfigurable PAs.
Collaborative Metric Learning Recommendation System: Application to Theatrical Movie Releases
Venue: ArXiv
Year: 2018

Product recommendation systems are important for major movie studios during the movie greenlight process and as part of machine learning personalization pipelines. Collaborative Filtering (CF) models have proved to be effective at powering recommender systems for online streaming services with explicit customer feedback data. CF models do not perform well in scenarios in which feedback data is not available, in cold start situations like new product launches, and situations with markedly different customer tiers (e.g. high frequency customers vs. casual customers) Generative natural language models that create useful theme based representations of an underlying corpus of documents can be used to represent new product descriptions, like new movie plots. When combined with CF, they have shown to increase the performance in cold start situations. Outside of those cases though in which explicit customer feedback is available, recommender engines must rely on binary purchase data, which materially degrades performance. Fortunately, purchase data can be combined with product descriptions to generate meaningful representations of products and customer trajectories in a convenient product space in which proximity represents similarity. Learning to measure the distance between points in this space can be accomplished with a deep neural network that trains on customer histories and on dense vectorizations of product descriptions. We developed a system based on Collaborative (Deep) Metric Learning (CML) to predict the purchase probabilities of new theatrical releases. We trained and evaluated the model using a large dataset of customer histories, and tested the model for a set of movies that were released outside of the training window. Initial experiments show gains relative to models that do not train on collaborative preferences.
Teaching Junior High School Chemistry During the COVID 19 Community Quarantine Season: Lessons, Challenges, And Opportunities
Year: 2020

This paper reports an autoethnographic study of a junior high school chemistry teacher's field experience in remote chemistry teaching during the Enhanced Community Quarantine (ECQ) brought by COVID 19 in the Philippines. The teaching of chemistry for Junior High School in an online setting is possible but has challenges as well. Rooted from the pedagogic data and selfnarration, this work examined the insights on the lessons, challenges and opportunities associated in teaching chemistry in basic education in an online mode. The researcher's online chemistry teaching experience can be recapped in an acronym "REACH OUT" Reinventing the wheel; Exploring the possibilities; Aligning to core essentials; Creating a learning routine; Hooking students online meaningfully; Offering consistent means of communication; Using authentic and reflective assessments; and Trusting the process. This paper, a pioneering of its kind, offers implications that can be embraced as we move into the new normal of having optimized online teaching experience and in shaping an undisruptive education that is responsive to crisis like the COVID 19 pandemic.
2018 ESC/EACTS Guidelines on myocardial revascularization.
Venue: European heart journal
Year: 2019

Authors/Task Force Members: Franz Josef Neumann* (ESC Chairperson) (Germany) Miguel Sousa Uva* (EACTS Chairperson) (Portugal) Anders Ahlsson (Sweden) Fernando Alfonso (Spain) Adrian P. Banning (UK) Umberto Benedetto (UK) Robert A. Byrne (Germany) Jean Philippe Collet (France) Volkmar Falk (Germany) Stuart J. Head (The Netherlands) Peter Juni (Canada) Adnan Kastrati (Germany) Akos Koller (Hungary) Steen D. Kristensen (Denmark) Josef Niebauer (Austria) Dimitrios J. Richter (Greece) Petar M. Seferovi c (Serbia) Dirk Sibbing (Germany) Giulio G. Stefanini (Italy) Stephan Windecker (Switzerland) Rashmi Yadav (UK) Michael O. Zembala (Poland) Document Reviewers: William Wijns (ESC Review Co ordinator) (Ireland) David Glineur (EACTS Review Co ordinator) (Canada) Victor Aboyans (France) Stephan Achenbach (Germany) Stefan Agewall (Norway) Felicita Andreotti (Italy) Emanuele Barbato (Italy) Andreas Baumbach (UK) James Brophy (Canada) Hector Bueno (Spain) Patrick A. Calvert (UK) Davide Capodanno (Italy) Piroze M. Davierwala
Design and Fabrication of the Mars Helicopter Rotor, Airframe, and Landing Gear Systems
Year: 2019

The Mars Helicopter is an autonomous 1.8 kg co axial, counter rotating rotorcraft baselined to fly on the Mars 2020 mission to demonstrate aerial mobility on the surface of Mars. In this paper the authors describe the design, development, and fabrication of the rotor system, landing gear system, and auxiliary structures which are being integrated onto the helicopter. The rotor system has a diameter of 1.21 m and consists of the rotor blades and hubs, direct drive brushless propulsion motors, swashplates and linkages, and servos that actuate the swashplate. The landing gear is comprised of four folding composite landing legs and suspension mechanisms that deploy upon egress from the rover. Several test campaigns were carried out on engineering development models in 2017/2018, and final assembly and testing of the flight model is expected to be complete by early spring 2019.
Perinatal depression, PTSD, and trauma: Impact on mother infant attachment and interventions to mitigate the transmission of risk
Venue: International review of psychiatry
Year: 2019

Early interactions between infants and their caregivers are fundamental to child development, and the parent infant relationship is believed to provide the foundation for healthy and secure attachment relationships and for infant mental health. Over time, these secure attachment relationships become the backbone for positive child outcomes across development. Abundant research to date confirms that parental mental illness, including depression and PTSD following trauma exposure, may have a detrimental impact on parenting quality and subsequent early child relationship formations. This review paper summarizes the literature on the role of sensitive parenting and a healthy mother infant relationship in establishing a secure mother infant attachment bond, which in turn is critical for the child's healthy socioemotional and cognitive development. The review also highlights the roles of maternal perinatal depression, PTSD, and/or exposure to interpersonal violence or childhood maltreatment onto parenting, bonding, and child attachment style towards the caregiver. The final section discusses existing therapeutic interventions and approaches that bolster early parenting practices and early maternal child relationships. Specific emphasis is placed on relational interventions that address bonding and attachment disturbances in the context of maternal perinatal mental health risk and trauma.
Fusing Aligned and Non aligned Face Information for Automatic Affect Recognition in the Wild: A Deep Learning Approach
Venue: 2016 IEEE Conference on Computer Vision and Pattern Recognition Workshops (CVPRW)
Year: 2016

Face alignment can fail in real world conditions, negatively impacting the performance of automatic facial expression recognition (FER) systems. In this study, we assume a realistic situation including non alignable faces due to failures in facial landmark detection. Our proposed approach fuses information about non aligned and aligned facial states, in order to boost FER accuracy and efficiency. Six experimental scenarios using discriminative deep convolutional neural networks (DCNs) are compared, and causes for performance differences are identified. To handle non alignable faces better, we further introduce DCNs that learn a mapping from non aligned facial states to aligned ones, alignment mapping networks (AMNs) We show that AMNs represent geometric transformations of face alignment, providing features beneficial for FER. Our automatic system based on ensembles of the discriminative DCNs and the AMNs achieves impressive results on a challenging database for FER in the wild.
Efficient Numerical Frameworks for Multi objective Cyber Security Planning
Venue: ESORICS
Year: 2016

We consider the problem of optimal investment in cyber security by an enterprise. Optimality is measured with respect to the overall (1) monetary cost of implementation, (2) negative side effects of cyber security controls (indirect costs) and (3) mitigation of the cyber security risk. We consider "passive" and "reactive" threats, the former representing the case where attack attempts are independent of the defender's plan, the latter, where attackers can adapt and react to an implemented cyber security defense. Moreover, we model in three different ways the combined effect of multiple cyber security controls, depending on their degree of complementarity and correlation. We also consider multi stage attacks and the potential correlations in the success of different stages. First, we formalize the problem as a non linear multi objective integer programming. We then convert them into Mixed Integer Linear Programs (MILP) that very efficiently solve for the exact Pareto optimal solutions even when the number of available controls is large. In our case study, we consider 27 of the most typical security controls, each with multiple intensity levels of implementation, and 37 common vulnerabilities facing a typical SME. We compare our findings against expert recommended critical controls. We then investigate the effect of the security models on the resulting optimal plan and contrast the merits of different security metrics. In particular, we show the superior robustness of the security measures based on the "reactive" threat model, and the significance of the hitherto overlooked role of correlations.
Cutting performance of CBN and diamond tools in dry turning of cemented carbide
Year: 2016

This research deals with the hard turning of cemented carbide with CBN and diamond tools, and focuses on the tool performance, mainly tool wear with respect to cutting force and cutting temperature. The internal turning tests without cutting fluid are executed with the vertical machining center. Seven types of tool materials: SC, CVD SC, two PCDs, BL NPD (Binderless nano polycrystalline diamond) and CBN: are selected for cutting three grades of cemented carbides WC having the different Co binder content (12% 20% and 25% Attrition has been found to be the main tool wear mechanism for all tools with slight adhesion of the workpiece binder on the tool face. In cutting of softest carbide WC m (25% Co) the polycrystalline CBN tool has the lowest tool wear than any other PCD tools. In turning of harder carbides WC d (20% Co) and WC t (12% Co) both polycrystalline CBN and PCD cannot be used continuously due to their low hardness, and BL NPD, SC and CVD SC tools are applicable. And the BL NPD tool has the best cutting performance with less flank wear. As for WC d, extremely stable cutting can be done with BL NPD where the principal cutting force is kept almost constant at 40 N. Only BL NPD tool can continue to turn the hardest WC t. In spite of turning hard materials, the tool temperatures measured are relatively low below 450degC due to the high thermal conductivities of tool materials. However, cutting temperature is directly related to the tool wear and cutting force rather than thermal conductivity of tool in turning of WC m and WC t.
Reference ranges of HOMA IR in normal weight and obese young Caucasians
Venue: Acta Diabetologica
Year: 2015

AimsInsulin resistance (IR) may develop very early in life being associated with occurrence of cardiometabolic risk factors (CMRFs) Aim of the present study was to identify in young Caucasians normative values of IR as estimated by the homeostasis model assessment (HOMA IR) and cutoffs diagnostic of CMRFs.MethodsAnthropometrics and biochemical parameters were assessed in 2753 Caucasians (age 2 17.8 years; 1204 F) Reference ranges of HOMA IR were defined for the whole population and for samples of normal weight and overweight/obese individuals. The receiver operator characteristic analysis was used to find cutoffs of HOMA IR accurately identifying individuals with any CMRF among total cholesterol and/or triglycerides higher than the 95th percentile and/or HDL cholesterol lower than the 5th for age and sex, impaired glucose tolerance, and alanine aminotransferase levels =40 U/l.ResultsOverweight/obese individuals had higher HOMA IR levels compared with normal weight peers (p 0.0001) at any age. HOMA IR index rose progressively with age, plateaued between age 13 and 15 years and started decreasing afterward. HOMA IR peaked at age 13 years in girls and at 15 years in boys. The 75th percentile of HOMA IR in the whole population (3.02; AUROC 0.73, 95 CI 0.70 0.75) in normal weight (1.68; AUROC 0.76, 95 CI 0.74 0.79) and obese (3.42; AUROC 0.71, 95 CI 0.69 0.72) individuals identified the cutoffs best classifying individuals with any CMRF.ConclusionsPercentiles of HOMA IR varied significantly in young Caucasians depending on sex, age, and BMI category. The 75th percentile may represent an accurate cutoff point to suspect the occurrence of one or more CMRFs among high total cholesterol and triglycerides, low HDL cholesterol, and ALT 40 UI/l.
Norms, Networks, Power, and Control: Understanding Informal Payments and Brokerage in Cross Border Trade in Sierra Leone
Year: 2018

Recent research has cast light on the variety of informal payments and practices that govern the day to day interactions between traders and customs agents at border posts in low income countries. Building on this literature, this paper draws on survey and qualitative evidence in an effort to explore which groups are most advantaged and disadvantaged by the largely informal processes and norms governing cross border trade. We find that understanding variation in strategies and outcomes across traders can only be effectively understood with reference to the importance of norms, networks, power, and the logic of control.
Biotechnological removal of H2S and thiols from sour gas streams under haloalkaline conditions
Year: 2016

Biotechnological removal of H2S and thiols from sour gas streams under haloalkaline conditions Pawel Roman Abstract Biological removal of H2S from sour gas streams became popular in recent years because of high process efficiency and low operational costs. To expand the scope of these processes to gas streams containing volatile organosulfur compounds, like thiols, it is necessary to provide new insights into their impact on overall biodesulfurization process. In the current thesis multidisciplinary investigations are performed, such as investigations of inhibitory effects of organic sulfur compounds on sulfide oxidizing biomass by biochemical and enzyme studies; modelling of the process performance and biological pathways; preparation of analytical tools for measuring unstable sulfur compounds under the process conditions; following the microbial dynamics. The research described in this thesis increases the understanding of the underlying processes occurring in biological gas desulfurization systems when organosulfur compounds are present in the feed gas and provides solutions how to cope with these compounds in full scale gas biodesulfurization installations.