Miracle-dz/UniFAR-FTUs huggingface dataset:
Adversarial Aacks on an Oblivious Recommender

Can machine learning models be easily fooled? Despite the recent surge of interest in learned adversarial attacks in other domains, in the context of recommendation systems this question has mainly been answered using hand-engineered fake user proles. This paper attempts to reduce this gap. We provide a formulation for learning to attack a recommender as a repeated general-sum game between two players, i.e., an adversary and a recommender oblivious to the adversary’s existence. We consider the challenging case of poisoning attacks, which focus on the training phase of the recommender model. We generate adversarial user proles targeting subsets of users or items, or generally the top-K recommendation quality. Moreover, we ensure that the adversarial user proles remain unnoticeable by preserving proximity of the real user rating/interaction distribution to the adversarial fake user distribution. To cope with the challenge of the adversary not having access to the gradient of the recommender’s objective with respect to the fake user proles, we provide a non-trivial algorithm building upon zero-order optimization techniques. We oer a wide range of experiments, instantiating the proposed method for the case of the classic popular approach of a low-rank recommender, and illustrating the extent of the recommender’s vulnerability to a variety of adversarial intents. These results can serve as a motivating point for more research into recommender defense strategies against machine learned attacks.
NATURAL BOUNDARY INTEGRAL METHOD AND ITS NEW DEVELOPMENT ∗1)

In this paper, the natural boundary integral method, and some related methods, including coupling method of the natural boundary elements and finite elements, which is also called DtN method or the method with exact artificial boundary conditions, domain decomposition methods based on the natural boundary reduction, and the adaptive boundary element method with hyper-singular a posteriori error estimates, are discussed. Mathematics subject classification: 65N38, 65N55, 65R20
Endoscopic Ultrasonography in the Diagnosis of Gastric Submucosal Tumor

Endoscopic ultrasonography (EUS) can display the gastric wall as a 5-layered structure corresponding to its histological layers. It can be used not only in differentiating gastric mural lesions from extragastric compression, also it can be used to delineate the size, location and extent of invasion of the submucosal tumors. From Oct. 1986 through July 1991, there were 31 cases which received EUS examination because of suspected gastric submucosal tumors. Histological diagnoses or documented extrinsic compression could be obtained in 23 cases. Of these, 20 cases (86.9%) were correctly diagnosed as to the origine of lesions but in only 15 cases (65.2%) were the ocrrect histological diagnoses made with EUS. Myogenic tumor is the most common gastric submucosal tumor; also, it is the tumor most frequently associated with reliable ultrasonic signs for histological diagnosis. Lymphoma & scirrhous carcinoma are other tumors in which EUS may make correct histological diagnosis but EUS tends to miss the subtle change of mucosa and thus may underestimate the extent of invasion. Although EUS is limited by lacking of specificity in differentiating between benign and malignant lesions and in making histological diagnoses of several kinds of submucosal tumors, it is still a useful tool when a suspected gastric submucosal tumor or a suspected extragastric compression is encountered.
A mathematical method for the turbulent behavior of crowds using agent particles

Among the people moving as a group there appear social and psychological forces together with physical forces such as friction and resistance. With the definition that the field of the crowd is the region of those forces continuously extending with varying strength, and with the pre-requisite that the spatial distribution of the crowd, i.e., the distribution of the field, varies according to the hydrodynamic rule by the Navier-Stokes equation, a methodology was proposed to describe the behavior of the crowd composed of many agent particles as the movement of a compressible, turbulent fluid. A numerical calculation was exemplified for the dynamic behavior and spatial distribution of crowds during movements when there appears a conflict between groups with different characters, imaging for instance the medieval battle of Breitenfeld.
Design of an Internet-Based Disease Management System for Chronic Heart Failure

Chronic diseases are one of the most challenging health problems in the world, and their burden on society is increasing. Managing these diseases using eHealth solutions could prove very beneficial, both in terms of economic costs and quality of life for patients. However, reaching these goals require knowledge in how to create distributed disease management systems for chronic diseases. In the project Care@Distance the aim is to acquire knowledge on how to use eHealth in order to improve treatment compliance in chronic diseases, improve possibilities for personalized care, alert about deteriorating health on an individual patient level, obtain acceptance among users (both care providers and patients), and finally introduce eHealth-based disease management systems into standard treatment procedures. This thesis covers one of these aims; designing for acceptance among users, mainly patients, but also care personnel. As a first step, the user group has been limited to only include patients with chronic heart failure, and the nurses connected to them. However, expanding general findings and experiences to other disorders should not cause any difficulties. Both the design process and the evaluation of two prototype systems will be covered in this thesis. The intention of the prototype systems was not to create a technically advanced and innovative system, but to produce a tool for attaining new knowledge about the issues related to introduction of eHealth-based disease management systems in Swedish health care. Both systems are described, the evaluations of the first prototype system are presented, and the results are discussed. Two patient related evaluations and one nurse survey have been performed, and the results indicate that the simple prototype system could be possible to transform into a solution suitable for use in the home of patients. Both the patient evaluations and the nurse survey also give insight into important issues to consider when designing an eHealth-based disease management system for chronic diseases. Especially important is the knowledge that one of the largest challenges will be handling of the information overflow related to regular collection of patient data. Future work includes evaluation and development of the second prototype system. The development of the prototype includes decision support for managing large amounts of patient data, and also increasing mobility of the system. Furthermore, additional measurement methods could be included in the prototype system in order to include special cases of patients, or other disorders.
Work related musculoskeletal disorders among nurses

A systematic review was conducted to study the current literature related to work related musculoskeletal disorders in nurses. A review was done using MEDLINE by the keywords “nurses”, “risk factors”, and “musculoskeletal disorders”. All the articles were reviewed by three reviewers based on the EPOC criteria and studies which were not adequate and inappropriate were excluded. Study design, type of data collection, assessment tools and outcomes obtained in the respective study were noted. Nurses were often required to lift heavy loads, work in awkward postures and transfer patients which were identified as the possible causes for acquiring WRMSDs.
Estimation of Subgraph Densities in Noisy Networks

Abstract While it is common practice in applied network analysis to report various standard network summary statistics, these numbers are rarely accompanied by uncertainty quantification. Yet any error inherent in the measurements underlying the construction of the network, or in the network construction procedure itself, necessarily must propagate to any summary statistics reported. Here we study the problem of estimating the density of an arbitrary subgraph, given a noisy version of some underlying network as data. Under a simple model of network error, we show that consistent estimation of such densities is impossible when the rates of error are unknown and only a single network is observed. Accordingly, we develop method-of-moment estimators of network subgraph densities and error rates for the case where a minimal number of network replicates are available. These estimators are shown to be asymptotically normal as the number of vertices increases to infinity. We also provide confidence intervals for quantifying the uncertainty in these estimates based on the asymptotic normality. To construct the confidence intervals, a new and nonstandard bootstrap method is proposed to compute asymptotic variances, which is infeasible otherwise. We illustrate the proposed methods in the context of gene coexpression networks. Supplementary materials for this article are available online.
Background Image Generation by Searching and Correcting Recent Partial Images

This paper proposes a novel method to generate a background image from sequential images captured by a fixed surveillance camera, which is effective also for the background subtraction method. In this method, the whole image region is divided into multiple lattice regions, for each of these regions a frame is selected from the recent images so as not to include any foregrounds in that region. It is experimentally confirmed that this method works well; it gives less noises and more precise foreground extraction than other existing methods for the background subtraction.
LSTMs , and Attention Networks for Pathology Detection in Medical Data

For the weakly supervised task of electrocardiogram (ECG) rhythm classification, convolutional neural networks (CNNs) and long short-term memory (LSTM) networks are two increasingly popular classification models. This work investigates whether a combination of both architectures to so-called convolutional long short-term memory (ConvLSTM) networks can improve classification performances by explicitly capturing morphological as well as temporal features of raw ECG records. In addition, various attention mechanisms are studied to localize and visualize record sections of abnormal morphology and irregular rhythm. The resulting saliency maps are supposed to not only allow for a better network understanding but to also improve clinicians’ acceptance of automatic diagnosis in order to avoid the technique being labeled as a black box. In further experiments, attention mechanisms are actively incorporated into the training process by learning a few additional attention gating parameters in a CNN model. An 8-fold cross validation is finally carried out on the PhysioNet Computing in Cardiology (CinC) challenge 2017 to compare the performances of standard CNN models, ConvLSTMs, and attention gated CNNs.
The Comparison of Post-Operative Pain between Topical Anesthesia and Monitored Anesthesia Care in Cataract Surgery

Purpose: To compare pain levels in cataract surgery under topical anesthesia only and topical anesthesia under monitored anesthesia care. Methods: We recruited 243 patients who were scheduled to undergo cataract surgery under topical anesthesia only or topical anesthesia with monitored anesthesia care (MAC) using fentanyl and midazolam. Anesthesia methods were selected based on the patient’s preference. All patients completed an anxiety and information scale survey preoperatively. Vital signs during the operations were recorded. A 0-to-10 visual analog scale pain score survey was conducted immediately and at 2 hours, 6 hours, and 1 day after surgery. Results: Of the 237 patients who completed the study, 183 patients selected topical anesthesia, and 54 patients selected MAC. Mean pain scores according to the aforementioned time points after surgery were 0.50, 0.58, 0.29, and 0.12 in the topical anesthesia group, and 0.22, 0.16, 0.06, and 0.09 in the MAC group, respectively. The differences in pain score between the two groups was statistically significant at 2 hours (p = 0.019) and 6 hours (p = 0.040) after surgery. The mean patient anxiety score for anesthesia was 10.50 in the topical anesthesia group and 11.41 in the MAC group (p = 0.280). Mean systolic blood pressure at the start of surgery was 140.6 mm Hg in the topical anesthesia group, and 158.2 mmHg in the MAC group. Conclusions: Monitored anesthesia care consistently resulted in less pain throughout the post-operative period. However, transient systolic blood pressure should be carefully monitored for a rise related to intravenous anesthetics. J Korean Ophthalmol Soc 2015;56(5):715-720
Automatic adjustment of genetic algorithm applied to the no-wait job shop problem

This paper describes a methodology of automatic genetic algorithm parameters adjustment dedicated to a job shop problem with a no-wait constraint with a makespan criterion. The numerical results show that in a given problem the efficiency of an algorithm with auto-tuning is placed at the level of an algorithm steered in a classical way with the best fit steering parameters.
Random Number Generation and Dvnamical System -Stat.istical Properties of Binary Sequences Generated by Oue-dimensional Maps-

$\mathrm{d}. \mathrm{i}_{1\mathrm{I}1\mathrm{C}11\mathrm{S}}. \cdot. \mathrm{i}_{011\mathrm{A}}1*\mathrm{I}\mathrm{l}\mathrm{l}\dot{\epsilon}\iota \mathrm{p}. \mathrm{s}. \cdot \mathrm{F}\mathrm{r}_{\wedge}\mathrm{o}\mathrm{m}$ $\mathrm{t}110-\mathrm{s}\mathrm{t}_{\dot{\mathrm{e}}1\mathrm{I}1(}1\mathrm{p}\mathrm{o}\mathrm{i}_{11}\mathrm{t}$ of$\mathrm{c}11\mathrm{g}\mathrm{i}11\mathrm{c}\cdot \mathrm{c}\mathrm{r}\mathrm{i}_{1\mathrm{l}}\mathrm{g}$ apph.catiollS-, it $\mathrm{i}_{\mathrm{S}\mathrm{u}\mathrm{c}\iota\cdot \mathrm{c}\mathrm{s}\mathrm{s}\mathrm{A}1}. \check{\gamma}\mathrm{t}0-$ evaluate
PNS1000398 73..81

Underand over-nutrition during pregnancy has been linked to the later development of diseases such as diabetes and obesity. Epigenetic modifications may be one mechanism by which exposure to an altered intrauterine milieu or metabolic perturbation may influence the phenotype of the organism much later in life. Epigenetic modifications of the genome provide a mechanism that allows the stable propagation of gene expression from one generation of cells to the next. This review highlights our current knowledge of epigenetic gene regulation and the evidence that chromatin remodelling and histone modifications play key roles in adipogenesis and the development of obesity. Epigenetic modifications affecting processes important to glucose regulation and insulin secretion have been described in the pancreatic b-cells and muscle of the intrauterine growth-retarded offspring, characteristics essential to the pathophysiology of type-2 diabetes. Epigenetic regulation of gene expression contributes to both adipocyte determination and differentiation in in vitro models. The contributions of histone acetylation, histone methylation and DNA methylation to the process of adipogenesis in vivo remain to be evaluated.
WST 49.10-T06 CORR

Activated sludge flocs consist of numerous constituents which, together with other factors, are responsible for floc structure and floc properties. These properties largely determine the sludge properties such as flocculation, settling and dewaterability. In this paper we briefly review the present knowledge about the role of bacteria in relation to floc and sludge properties, and we present a new approach to investigate the identity and function of the bacteria in the activated sludge flocs. The approach includes identification of the important bacteria and a characterization of their physiological and functional properties. It is carried out by use of culture-independent molecular biological methods linked with other methods to study the physiology and function, maintaining a single cell resolution. Using this approach it was found that flocforming properties differed among the various bacterial groups, e.g. that different microcolony-forming bacteria had very different sensitivities to shear and that some of them deflocculated under anaerobic conditions. In our opinion, the approach to combine identity with functional analysis of the dominant bacteria in activated sludge by in situ methods is a very promising way to investigate correlations between presence of specific bacteria, and floc and sludge properties that are of interest.
From Single Atoms to Engineered ‘‘Super-Atoms’’: Interfacing Photons and Atoms in Free Space

During the last decades the development of laser cooling and trapping has revolutionized the field of quantumoptics.Nowwemaster techniques to control the quantum properties of atoms and light, even at a single atom and single photon level. Understanding and controlling interactions of atoms and light both on the microscopic single particle and on the macroscopic collective levels, are two of the very active directions of the current research in this field. The goal is to engineer quantum systems with tailored properties designed for specific applications. One of the ambitious applications on this way is interfacing quantum information for quantum communication and quantum computing. We summarize here theoretical ideas and experimental methods for interfacing atombased quantum memories with single flying photons.
Reports and Reviews: Book Review

waste and using aerated windrow composting for a relative short period of time. (4) Financing. Papers prepared by G. Teufel, R. Maus and H. Gerlt (West Germany) gave a thorough description of all aspects of financial arrangements concerning purchase of a plant. (5) Selection of waste refinement plants/systems. Technical and legal questions relating to purchase of a plant were discussed by R. Csokay (Austria), and A. Urban (West Germany) described in detail the necessary planning steps in order to make a realistic comparison of different plant offers prior to selection of a specific plant or system.
PPAR and cardiovascular risk

In this Review in Depth on ‘PPAR and Cardiovascular Ž Risk’, Marx et al. describe the role of PPARs per. oxisome proliferator-activated receptors in the vessel wall and their putative role in cardiovascular disease, while Duez et al. focus particularly on the effects of PPARs in inflammation, atherosclerosis and thrombosis. Kaplan et al. review the effects of PPARs in insulin resistance and in type 2 diabetes and Robins describes clinical results showing that PPAR ligands reduce cardiovascular risk, particularly in patients with insulin insensitivity.
Interference of fetal hemoglobin in the determination of carboxyhemoglobin by spectrophotometry

ABSTRACT Determination of carboxyhemoglobin (HbCO) is routinely performed in suspected cases of carbon monoxide intoxication and unexplained deaths. However, some authors have suggested that measured HbCO may be falsely elevated in infants (0–12 months) due to the presence of fetal hemoglobin (HbF). The purpose of this study was to evaluate the impact of fetal hemoglobin on the spectro-photometric determination of carboxyhemoglobin. The interference of HbF in the determination of HbCO in infants aged from 0 to 12 months was evaluated using 16 ante-mortem and 19 post-mortem blood samples. The %HbCO was quantified spectrophotometrically by calculating the 560 nm/530 nm absorbance ratio, using a dual-beam spectrophotometer. The average measured HbCO in infants of 3 months of age or under was 17%, which is abnormally elevated. No significant difference in HbCO measurement was found between ante-mortem and post-mortem samples. These results highlight the fact that care must be taken in interpretation of carboxyhemoglobin measurements in infants when using a spectrophotometric method.
Investigation of ephaptic interactions in peripheral nerve of sheep using 6 kHz subthreshold currents

The objective of this work was to determine whether application of subthreshold currents to the peripheral nerve increases the excitability of the underlying nerve fibres, and how this increased excitability would alter neural activity as it propagates through the subthreshold currents. Experiments were performed on two Romney cross-breed sheep in vivo, by applying subthreshold currents either at the stimulus site or between the stimulus and recording sites. Neural recordings were obtained from nerve cuff implanted on the peroneal or sciatic nerve branches, while stimulus was applied to either the peroneal nerve or pins placed through the lower hindshank. Results showed that subthreshold currents applied to the same site as stimulus increased excitation of underlying nerve fibres (p < 0.0001). With stimulus and subthreshold currents applied to different sites on the peroneal nerve, the primary CAP in the sciatic displayed a temporal shift of -2.5 to -3 us which agreed with statistically significant changes in the CAP waveform (p<0.02). These findings contribute to the understanding of mechanisms in myelinated fibres of subthreshold current neuromodulation therapies.
Exploration of neural machine translation in autoformalization of mathematics in Mizar

In this paper we share several experiments trying to automatically translate informal mathematics into formal mathematics. In our context informal mathematics refers to human-written mathematical sentences in the LaTeX format; and formal mathematics refers to statements in the Mizar language. We conducted our experiments against three established neural network-based machine translation models that are known to deliver competitive results on translating between natural languages. To train these models we also prepared four informal-to-formal datasets. We compare and analyze our results according to whether the model is supervised or unsupervised. In order to augment the data available for auto-formalization and improve the results, we develop a custom type-elaboration mechanism and integrate it in the supervised translation.
Fingerprint Spoof Generalization

We present a style-transfer based wrapper, called Universal Material Generator (UMG), to improve the generalization performance of any fingerprint spoof detector against spoofs made from materials not seen during training. Specifically, we transfer the style (texture) characteristics between fingerprint images of known materials with the goal of synthesizing fingerprint images corresponding to unknown materials, that may occupy the space between the known materials in the deep feature space. Synthetic live fingerprint images are also added to the training dataset to force the CNN to learn generative-noise invariant features which discriminate between lives and spoofs. The proposed approach is shown to improve the generalization performance of a state-of-the-art spoof detector, namely Fingerprint Spoof Buster, from TDR of 75.24% to 91.78% @ FDR = 0.2%. These results are based on a large-scale dataset of 5,743 live and 4,912 spoof images fabricated using 12 different materials. Additionally, the UMG wrapper is shown to improve the average cross-sensor spoof detection performance from 67.60% to 80.63% when tested on the LivDet 2017 dataset. Training the UMG wrapper requires only 100 live fingerprint images from the target sensor, alleviating the time and resources required to generate large-scale live and spoof datasets for a new sensor. We also fabricate physical spoof artifacts using a mixture of known spoof materials to explore the role of cross-material style transfer in improving generalization performance.