Miracle-dz/UniFAR-FTUs huggingface dataset:
On the Implementation and Assessment of several Divide & Conquer Matheuristic Strategies for the solution of the Knapsack Problem

We introduce and asses a Divide \& Conquer heuristic method, aimed to solve large instances of the Knapsack Problem. The method subdivides a large problem in two smaller ones (or recursive iterations of the same principle), to lower down the global computational complexity of the original problem, at the expense of a moderate loss of quality in the solution. Theoretical mathematical results are presented in order to guarantee an algorithmically successful application of the method and to suggest the potential strategies for its implementation. In contrast, due to the lack of theoretical results, the solution's quality deterioration is measured empirically by means of Monte Carlo simulations for several types and values of the chosen strategies. Finally, introducing parameters of efficiency we suggest the best strategies depending on the data input.
Please Forget Where I Was Last Summer: The Privacy Risks of Public Location (Meta)Data

The exposure of location data constitutes a significant privacy risk to users as it can lead to de-anonymization, the inference of sensitive information, and even physical threats. In this paper we present LPAuditor, a tool that conducts a comprehensive evaluation of the privacy loss caused by publicly available location metadata. First, we demonstrate how our system can pinpoint users' key locations at an unprecedented granularity by identifying their actual postal addresses. Our experimental evaluation on Twitter data highlights the effectiveness of our techniques which outperform prior approaches by 18.9%-91.6% for homes and 8.7%-21.8% for workplaces. Next we present a novel exploration of automated private information inference that uncovers "sensitive" locations that users have visited (pertaining to health, religion, and sex/nightlife). We find that location metadata can provide additional context to tweets and thus lead to the exposure of private information that might not match the users' intentions. We further explore the mismatch between user actions and information exposure and find that older versions of the official Twitter apps follow a privacy-invasive policy of including precise GPS coordinates in the metadata of tweets that users have geotagged at a coarse-grained level (e.g., city). The implications of this exposure are further exacerbated by our finding that users are considerably privacy-cautious in regards to exposing precise location data. When users can explicitly select what location data is published, there is a 94.6% reduction in tweets with GPS coordinates. As part of current efforts to give users more control over their data, LPAuditor can be adopted by major services and offered as an auditing tool that informs users about sensitive information they (indirectly) expose through location metadata.
Risk-aware Multi-armed Bandits Using Conditional Value-at-Risk

Traditional multi-armed bandit problems are geared towards finding the arm with the highest expected value -- an objective that is risk-neutral. In several practical applications, e.g., finance, a risk-sensitive objective is to control the worst-case losses and Conditional Value-at-Risk (CVaR) is a popular risk measure for modelling the aforementioned objective. We consider the CVaR optimization problem in a best-arm identification framework under a fixed budget. First, we derive a novel two-sided concentration bound for a well-known CVaR estimator using empirical distribution function, assuming that the underlying distribution is unbounded, but either sub-Gaussian or light-tailed. This bound may be of independent interest. Second, we adapt the well-known successive rejects algorithm to incorporate a CVaR-based criterion and derive an upper-bound on the probability of incorrect identification of our proposed algorithm.
A probabilistic framework for tracking uncertainties in robotic manipulation

Precisely tracking uncertainties is crucial for robots to successfully and safely operate in unstructured and dynamic environments. We present a probabilistic framework to precisely keep track of uncertainties throughout the entire manipulation process. In agreement with common manipulation pipelines, we decompose the process into two subsequent stages, namely perception and physical interaction. Each stage is associated with different sources and types of uncertainties, requiring different techniques. We discuss which representation of uncertainties is the most appropriate for each stage (e.g. as probability distributions in SE(3) during perception, as weighted particles during physical interactions), how to convert from one representation to another, and how to initialize or update the uncertainties at each step of the process (camera calibration, image processing, pushing, grasping, etc.). Finally, we demonstrate the benefit of this fine-grained knowledge of uncertainties in an actual assembly task.
Multi-Model authentication using keystroke dynamics for Smartphones

By the year 2018 it is predicted that 84% of the total world’s population would own a smartphone device. Intruders that gain access to someone’s phone can easily obtain personal and sensitive data about them, such as emails and messages, or even impersonate the rightful owner. Although an intruder can easily get the owner’s smartphone’s password by looking over their shoulder, it would be very hard for them to match the owner’s typing signature. However if the owner’s typing signature is only based on one typing mode, such as standing still and typing with one hand, it would be very inconvenient for the owner to always stand still and type with one hand as otherwise they’d likely be marked as intruders and get frustrated over time. This research addresses exactly this. We found that models covering different typing modes and activities such as standing or moving and typing one handed or two handed, can be achieved with Equal Error Rate values as low as 0.44%. The best results were achieved using a Least Squares SVM classifier with RBF kernel. We also explore and discuss any differences in classifying between typing activities, Digraphs vs Trigraphs, feature importance, misclassification analyses and full typing sessions vs sentence by sentence based classification.
Proposal of Novel MPTCP Congestion Control to Suppress QoS Fluctuation for WebQoE Improvement

This paper proposes a new congestion control of Multi-Path TCP (MPTCP) for improvement of Quality of Experience (QoE). This method controls the congestion window for each subflow so as to suppress the fluctuation of Quality of Service (QoS). The fluctuation of QoS is estimated from that of the Round Trip Time, and the congestion window is controlled according to the estimated fluctuation. The authors implemented the proposed method and evaluate QoS by experiment. The experimental results show that the proposed method can suppress the fluctuation of QoS as compared with the existing congestion controls of MPTCP under congestion.
Activity monitoring from RGB input for indoor action recognition systems

In this work we present how some state-of-the art action recognition techniques can be tailored to monitoring indoor human activities. At first, we analyze the most relevant algorithms and eventually we present an effective implementation based on the solely RGB input. Our preliminary results show that the proposed solution achieves competitive results with respect to other methods in the state of the art that take also advantage of multiple inputs.
Personalized TV Distribution to Adaptive HTTP Streaming Clients

There is a growing interest in delivering personalized viewing experiences where the media content is tailored to the individual user. Personalized advertisements are used today by content providers to enhance user experience and increase revenue. The impact of personalized media distribution on the end-to-end system, in particular Content Delivery Networks (CDNs), is largely unstudied. In this paper, we study the delivery of personalized TV to a plurality of streaming clients leveraging adaptive HTTP streaming technologies. A personalized TV channel is composed of a sequence of video and Ad slots which are customized for the user. We quantify the personalization overhead and propose different approaches for efficient delivery of personalized DASH content. Results from a CDN simulator indicate that significant reductions in CDN traffic and storage requirements can be achieved without deteriorating the streaming bitrate of the clients.
IVLFood-WS: Recognizing food in the wild using Deep Learning

In this paper we present a system for food recognition in the wild, implemented as a set of web services (IVLFood-WS). It integrates different solutions based on Deep Learning and Convolutional Neural Networks that we have developed in recent years within past and ongoing projects. The system tackles different aspects of image food analysis such as food localization, classification and retrieval. Results show that a complete system that integrates our solutions can be effectively exploited for supporting user in keeping track of their daily food consumption in uncontrolled environment (i.e. in the wild).
Optical Character Recognition on images with colorful background

In this paper, a preprocessing method is presented for improving Tesseract Optical Character Recognition (OCR) performance on images with colorful background. The proposed method consists of two steps. At first, a text segmentation method is performed which attempts to extract the text from the colorful background. This step is based on input image clustering into k images. In the second step, a classifier is used to identify the image containing text among k images resulting from the previous step. OCR is then performed on the identified image. The proposed preprocessing method improves Tesseract OCR performance by approximately 20%.
Driver Monitoring implementation in Adaptive AUTOSAR environment

Advanced Driver Assistance System (ADAS) algorithms are of significant importance in the modern automotive industry. The algorithms have changed the approach to two important issues of the industry: traffic efficiency, and safety. ADAS algorithms have very demanding requirements, such as real time execution and low memory consumption. Thus, one of the main challenges is to satisfy these requirements without compromising the reliability. Although all components that add to the safety are important, one that is most commonly addressed is drowsiness detection, because the drowsiness is at the top causes of traffic accidents. Automotive grade standards have changed periodically to include and tailor recent techniques and models. In this paper, we present driver drowsiness detection solution which is implemented on the Adaptive AUTOSAR platform.
The Association of Adiponectin and Visceral Fat with Insulin Resistance and β-Cell Dysfunction

Background Obesity is a risk factor for metabolic abnormalities. We investigated the relationship of adiponectin levels and visceral adiposity with insulin resistance and β-cell dysfunction. Methods This cross-sectional study enrolled 1,347 participants (501 men and 846 women aged 30–64 years) at the Cardiovascular and Metabolic Diseases Etiology Research Center. Serum adiponectin levels and visceral fat were measured using enzyme-linked immunosorbent assay kits and dual-energy X-ray absorptiometry, respectively. Insulin resistance was evaluated using the homeostatic model assessment of insulin resistance (HOMA-IR) and Matsuda insulin sensitivity index. β-cell dysfunction was evaluated using the homeostatic model assessment of β-cell function (HOMA-β), insulinogenic index, and disposition index. Results Regarding insulin resistance, compared with individuals with the highest adiponectin levels and visceral fat mass < 75th percentile, the fully adjusted odds ratios (ORs) for HOMA-IR ≥ 2.5 and Matsuda index < 25th percentile were 13.79 (95% confidence interval, 7.65–24.83) and 8.34 (4.66–14.93), respectively, for individuals with the lowest adiponectin levels and visceral fat ≥ 75th percentile. Regarding β-cell dysfunction, the corresponding ORs for HOMA-β < 25th percentile, insulinogenic index < 25th percentile, and disposition index < 25th percentile were 1.20 (0.71–2.02), 1.01 (0.61–1.66), and 1.87 (1.15–3.04), respectively. Conclusion Low adiponectin levels and high visceral adiposity might affect insulin resistance and β-cell dysfunction.
Metformin improves diastolic function in an HFpEF-like mouse model by increasing titin compliance

&NA; Heart failure with preserved ejection fraction (HFpEF) is a complex syndrome characterized by a preserved ejection fraction but increased diastolic stiffness and abnormalities of filling. Although the prevalence of HFpEF is high and continues to rise, no effective therapies exist; however, the diabetic drug metformin has been associated with improved diastolic function in diabetic patients. Here we determine the therapeutic potential of metformin for improving diastolic function in a mouse model with HFpEF‐like symptoms. We combine transverse aortic constriction (TAC) surgery with deoxycorticosterone acetate (DOCA) supplementation to obtain a mouse model with increased diastolic stiffness and exercise intolerance. Echocardiography and pressure‐volume analysis reveal that providing metformin to TAC/DOCA mice improves diastolic function in the left ventricular (LV) chamber. Muscle mechanics show that metformin lowers passive stiffness of the LV wall muscle. Concomitant with this improvement in diastolic function, metformin‐treated TAC/DOCA mice also demonstrate preserved exercise capacity. No metformin effects are seen in sham operated mice. Extraction experiments on skinned ventricular muscle strips show that the metformin‐induced reduction of passive stiffness in TAC/DOCA mice is due to an increase in titin compliance. Using phospho‐site‐specific antibodies, we assay the phosphorylation of titin's PEVK and N2B spring elements. Metformin‐treated mice have unaltered PEVK phosphorylation but increased phosphorylation of PKA sites in the N2B element, a change which has previously been shown to lower titin's stiffness. Consistent with this result, experiments with a mouse model deficient in the N2B element reveal that the beneficial effect of metformin on LV chamber and muscle stiffness requires the presence of the N2B element. We conclude that metformin offers therapeutic benefit during HFpEF by lowering titin‐based passive stiffness. &NA; Heart failure with preserved ejection fraction (HFpEF) is a syndrome characterized by increased diastolic stiffness, for which effective therapies are lacking. Slater et al. show that metformin lowers titin‐based passive stiffness in an HFpEF mouse model and may therefore be of therapeutic benefit.
Successful Treatment of Catheter Related Blood Stream Infection By Millerozyma farinosa with Micafungin: A Case Report

Millerozyma farinosa (formerly Pichia farinosa) is halotolerant yeast mainly found in food and ubiquitous in the environment. It was a rare yeast pathogen, but it has recently emerged as a cause of fungemia in immunocompromised patients. Optimal therapy for invasive fungal infection by this pathogen remains unclear. We report a case of catheter related blood stream infection caused by M. farinosa in a 71-year-old patient who recovered successfully after removal of the central venous catheter and treatment with micafungin.
Natal habitat preference induction in large mammals—Like mother, like child?

Abstract Habitat selection has received considerable attention from ecologists during the last decades, yet the underlying forces shaping individual differences in habitat selection are poorly documented. Some of these differences could be explained by the early experience of individuals in their natal habitat. By selecting habitat attributes like those encountered early in life, individuals could improve resource acquisition, survival, and ultimately fitness. This behavior, known as natal habitat preference induction (NHPI), could be particularly common in large mammals, because offspring generally stay with their mother for an extended period. We used three complementary approaches to assess NHPI in a marked population of woodland caribou (Rangifer tarandus caribou): (a) population‐based resource selection functions (RSFs), (b) individual‐based RSFs, and (c) behavioral repeatability analyses. All approaches compared the behavior of calves in their natal range to their behavior as independent subadults during the snow‐covered (Dec–Apr) and snow‐free (May–Nov) seasons. Using RSFs, we found that the magnitude of habitat selection between calf and subadult stages differed for most covariates, yet the signs of statistically significant effects (selection vs. avoidance) were generally the same. We also found that some habitat selection tactics were highly repeatable across life stages. Notably, caribou responses to habitat disturbances were highly repeatable year‐round, meaning that different individuals reacted differently, but consistently, to disturbances. This study highlights the potential role of natal habitat preference induction in shaping individual differences in habitat selection in large mammals and provides valuable knowledge for the management and conservation of a threatened species.
Linking beaver dam affected flow dynamics to upstream passage of Arctic grayling

Abstract Beaver reintroductions and beaver dam structures are an increasingly utilized ecological tool for rehabilitating degraded streams, yet beaver dams can potentially impact upstream fish migrations. We collected two years of data on Arctic grayling movement through a series of beaver dams in a low gradient mountain stream, utilizing radio‐telemetry techniques, to determine how hydrology, dam characteristics, and fish attributes impeded passage and movement rates of spawning grayling. We compared fish movement between a “normal” flow year and a “low” flow year, determined grayling passage probabilities over dams in relation to a suite of factors, and predicted daily movement rates in relation to the number of dams each fish passed and distance between dams during upstream migration to spawning areas. We found that the average passage probability over unbreached beaver dams was 88%, though we found that it fell below 50% at specific dams. Upstream passage of grayling was affected by three main characteristics: (a) temperature, (b) breach status, and (c) hydrologic linkages that connect sections of stream above and below the dam. Other variables influence passage, but to a lesser degree. Cumulative passage varied with distance upstream and total number of dams passed in low versus normal flow years, while movement rates upstream slowed as fish swam closer to dams. Our findings demonstrate that upstream passage of fish over beaver dams is strongly correlated with hydrologic conditions with moderate controls by dam‐ and fish‐level characteristics. Our results provide a framework that can be applied to reduce barrier effects when and where beaver dams pose a significant threat to the upstream migration of fish populations while maintaining the diverse ecological benefits of beaver activity when dams are not a threat to fish passage.
Pathological Process of Prompt Connection between Host and Donor Tissue Vasculature Causing Rapid Perfusion of the Engineered Donor Tissue after Transplantation

The shortage of donors for transplantation therapy is a serious issue worldwide. Tissue engineering is considered a potential solution to this problem. Connection and perfusion in engineered tissues after transplantation is vital for the survival of the transplanted tissue, especially for tissues requiring blood perfusion to receive nutrients, such as the heart. A myocardial cell sheet containing an endothelial cell network structure was fabricated in vitro using cell sheet technology. Transplantation of the three-dimensional (3D) tissue by layering myocardial sheets could ameliorate ischemic heart disease in a rat model. The endothelial cell network in the 3D tissue was able to rapidly connect to host vasculature and begin perfusion within 24 h after transplantation. In this review, we compare and discuss the engineered tissue–host vasculature connection process between tissue engineered constructs with hydrogels and cell sheets by histological analysis. This review provides information that may be useful for further improvements of in vivo engineered tissue vascularization techniques.
Gut Microbial Metabolism and Nonalcoholic Fatty Liver Disease

The gut microbiome, the multispecies community of microbes that exists in the gastrointestinal tract, encodes several orders of magnitude more functional genes than the human genome. It also plays a pivotal role in human health, in part due to metabolism of environmental, dietary, and host‐derived substrates, which produce bioactive metabolites. Perturbations to the composition and associated metabolic output of the gut microbiome have been associated with a number of chronic liver diseases, including nonalcoholic fatty liver disease (NAFLD). Here, we review the rapidly evolving suite of next‐generation techniques used for studying gut microbiome composition, functional gene content, and bioactive products and discuss relationships with the pathogenesis of NAFLD.
Effectiveness of inactivated hantavirus vaccine on the disease severity of hemorrhagic fever with renal syndrome

Background An inactivated Hantaan virus vaccine (iHV) has been broadly used as a preventive strategy for hemorrhagic fever with renal syndrome (HFRS) by the South Korean Army. After the vaccination program was initiated, the overall incidence of HFRS cases was reduced in the military population. While there are about 400 HFRS cases annually, few studies have demonstrated the efficacy of the iHV in field settings. Therefore, this study aimed to evaluate the iHV efficacy on HFRS severity. Methods From 2009 to 2017, HFRS cases were collected in South Korean Army hospitals along with patients’ vaccination history. HFRS patients were classified retrospectively into two groups according to vaccination records: no history of iHV vaccination and valid vaccination. Vaccine efficacy on the severity of acute kidney injury (AKI) stage and dialysis events were investigated. Results The effects of the iHV on renal injury severity in between 18 valid vaccinated and 110 non-vaccinated patients were respectively evaluated. In the valid vaccination group, six of the 18 HFRS patients (33.3%) had stage 3 AKI, compared to 60 of the 110 (54.5%) patients in the non-vaccination group. The iHV efficacy against disease progression (VEp) was 58.1% (95% confidence interval, 31.3% to 88.0%). Conclusion The iHV efficacy against the progression of HFRS failed to demonstrate statistically significant protection. However, different severity profiles were observed between the iHV and non-vaccination groups. Additional studies with larger populations are needed to demonstrate the effectiveness of the iHV in patients with HFRS.