Miracle-dz/UniFAR-FTUs huggingface dataset:
Automatic segmentation of low-grade brain tumor using a random forest classiﬁer and Gabor features

—Computerized tumor detection and segmentation algorithms are developed to assist the work medical staff at the diagnosis or therapy planning. This paper presents a procedure trained to segment low-grade gliomas in multispectral volumetric MRI records. The proposed solution employs a random forest classiﬁer based on 104 morphological and Gabor wavelet features. A neighborhood-based post-processing was designed to regularize the output of the classiﬁer. The current version of our system was trained and tested using all 54 low-grade tumor volumes from the MICCAI BRATS 2016 database. The achieved accuracy is characterized by an overall mean Dice score of 83 . 8% , sensitivity > 85% , and speciﬁcity > 98% . The proposed method is likely to detect all gliomas of 2 cm diameter.
Naming, Assigning and Registering Identiﬁers in a Locator/Identiﬁer-Split Internet Architecture

—Splitting the IP-address into locator and identiﬁer seems to be a promising approach for a Future Internet Architecture. Although this solution addresses the most critical issues of today’s architecture, new challenges arise through the necessary mapping system to resolve identiﬁers into the corresponding locators. In this work, we give an overview of a scheme how to name identiﬁers not only for hosts, but basically for anything that needs to be identiﬁed in a future Internet. Our approach is based on the HiiMap locator/ID split Internet architecture and supports user-friendly identiﬁers for hosts, content, and persons and does not rely on DNS. We show how the registration and assignment for identiﬁers is handled and which modiﬁcations in the network stack are necessary. Furthermore, a possible solution for a lookup mechanism that can deal with spelling mistakes and typing errors in order to improve the quality of experience to the user is provided.
- Hepatitis B Virus Infection through PD-1 Immune Response in Patients with Chronic Myeloid-Derived Suppressor Cells Regulate

Although myeloid-derived suppressor cells (MDSCs) are well known for their immunosuppressive function in several pathological conditions, the role of MDSCs in hepatitis B virus infection remains obscure. In this study, we investigated the frequency and function of MDSCs in the peripheral blood and liver of 91 chronic hepatitis B (CHB) patients. A higher percentage of MDSCs, deﬁned as CD14 + HLA-DR 2 /low , was detected in peripheral blood of CHB patients than that of the healthy controls. Moreover, high expression of programmed death 1 (PD-1) and secretion of IL-10 in this population were determined. The frequency of MDSCs was positively correlated with serum viral load, but it was negatively correlated with liver inﬂammatory injury. These cells were also abundant in liver tissue of CHB patients and were related to necroinﬂammatory activity. Furthermore, we found that these cells could suppress hepatitis B virus–speciﬁc CD8 + T cell response, including reduced proliferation and IFN- g production, and inhibit degranulation of CD8 + T cells, including reduced production of granzyme B and perforin. Importantly, PD-1–induced IL-10 production by MDSCs was responsible for the suppressive activity. To our knowledge, for the ﬁrst time our study proved that CD14 + HLA-DR –/low PD-1 + MDSCs in CHB patients contribute to an inadequate immune response against the virus and lead to chronic infection, which represents a potential target for therapeutic intervention. The Journal of Immunology , 2014, 193: 000–000. to determine whether are the to We that patients with chronic HBV infection have a higher of compared with controls and that are responsible for the inability of infection for patients. For this we investigated the frequency, phenotype, and function of MDSCs in chronic HBV patients and evaluated the association of MDSCs with disease
Recycling production cable waste : environmental and economic aspects

The main driver for recycling cable wastes is the high value of the conducting metal, while the plastic with its lower value is often neglected. New improved cable plastic recycling routes could provide both economic and environmental incentive to cable producers for moving up the "cable plastic waste ladder". The improvement potential for the European cable industry as a whole is roughly estimated to avoidance of 30 750 tonnes of CO2eq annually if these new techniques were to be applied to the 5% plastic waste stream from cable production. Cradle-to-gate life cycle assessment of the waste management of the cable scrap is suggested and explained as a method to analyze the pros and cons of different cable scrap recycling options at hand. Economic and environmental data about different recycling processes and other relevant processes and materials are given. Cable producers could use this data and method to assess the way they deal with the cable plastic waste today and compare it with available alternatives and thus illuminate the improvement potential of recycling cable plastic waste. Through using the data and methods provided, the user will be able to show the climate impacts of improving the cable waste recycling (compared to how it is done today) and also to show the economic and technical implications of such improvements.
Combining Hard and Soft Aspects in Project Performance Measurement - A Qualitative Research Undertaken in an Agile Software Development Project Scenario

Generally, in agile software development projects, project performance is measured using Key Performance Indicators that are focused exclusively on the project’s deliverables to the customer. The softer aspects concerning the smooth functioning of agile teams are usually understood in the traditional manner through meetings, group discussions and surveys and there is an air of informality around it like every other method. But with increasing project complexity, team sizes have increased and projects have been pursued with virtual teams located across the world. Even in such scenarios, the way hard and soft aspects are dealt with has not undergone a change. The research aims to qualitatively explore the possibilities of combining hard and soft aspects as KPIs in such environments to measure project performance more effectively. The research is an abductive case study of a complex agile software development project in the automotive sector. Interviews and questionnaires were conducted, ably supported by participant observations with two levels of the project organization and internal data from the organization. The study aims to link the findings with existing theory in agile methodology and project performance measurements. The gaps existing in agile methodology are viewed through the lens of project performance and the final findings are arrived at. The most striking finding was about managers knowing the need of soft aspects for project performance but assumed the informal meetings brought up these issues. On the contrary, the operational level employees voiced their concern about many soft issues which had not been escalated before. The findings uncovered a gap in agile methodology regarding the balance between focus on the external customer and getting internal stakeholders committed to that purpose. The researchers have attempted to visualize the combination of these two aspects, through the use of the GQM model. It was possible to conclude that in complex project environments governed by a short and engaging planning cycle, project performance cannot be fully understood based on the deliveries made to the customer. The soft aspects of the project team should also be viewed in a formalized way as KPIs to get a complete idea about project performance.
Model Reconstruction: Mining Test Cases

—System monitors need oracles to determine whether observed traces are acceptable. One method is to compare the observed traces to a formal model of the sys-tem. Unfortunately, such models are not always available — software may be developed without generating a formal model, or the implementation deviates from the original speciﬁcation. In previous work, we have proposed a learning algorithm to construct a formal model of the software from its test cases, thereby providing a means to transform test cases for ofﬂine testing into an oracle for monitoring. In this paper, we reﬁne our learning algorithm with a set of state-merging rules that help to exploit the test cases for additional information. Using the additional information mined from the test cases, models can be learned from smaller test suites.
Improve Privacy Policy Inference Model for Network Communication Using Enhanced Parent Policy Control Algorithm

: In recent years, a tremendous growth is seen in online social network. These online social networks offer attractive means for digital social interactions and information sharing, but also raise some security and privacy issues. While online social networks allow users to restrict access to shared data (policy mining), they currently do not provide any mechanism to enforce privacy concerns over data associated with multiple users. Also, it analyzes how the approach can affect the effectiveness of a policy-based collaborative tagging system that supports enhanced web access functionalities, like content filtering and discovery, based on preferences specified by end users.
Memristor Platforms for Pattern Recognition Memristor Theory, Systems and Applications

In the last decade a large scientific community has focused on the study of the memristor. The memristor is thought to be by many the best alternative to CMOS technology, which is gradually showing its flaws. Transistor technology has developed fast both under a research and an industrial point of view, reducing the size of its elements to the nano-scale. It has been possible to generate more and more complex machinery and to communicate with that same machinery thanks to the development of programming languages based on combinations of boolean operands. Alas as shown by Moore's law, the steep curve of implementation and of development of CMOS is gradually reaching a plateau. It is clear the need of studying new elements that can combine the efficiency of transistors and at the same time increase the complexity of the operations. Memristors can be described as non-linear resistors capable of maintaining memory of the resistance state that they reached. From their first theoretical treatment by Professor Leon O. Chua in 1971, different research groups have devoted their expertise in studying the both the fabrication and the implementation of this new promising technology. In the following thesis a complete study on memristors and memristive elements is presented. The road map that characterizes this study departs from a deep understanding of the physics that govern memristors, focusing on the HP model by Dr. Stanley Williams. Other devices such as phase change memories (PCMs) and memristive biosensors made with Si nano-wires have been studied, developing emulators and equivalent circuitry, in order to describe their complex dynamics. This part sets the first milestone of a pathway that passes trough more complex implementations such as neuromorphic systems and neural networks based on memristors proving their computing efficiency. Finally it will be presented a memristror-based technology, covered by patent, demonstrating its efficacy for clinical applications. The presented system has been designed for detecting and assessing automatically chronic wounds, a syndrome that affects roughly 2% of the world population, through a Cellular Automaton which analyzes and processes digital images of ulcers. Thanks to its precision in measuring the lesions the proposed solution promises not only to increase healing rates, but also to prevent the worsening of the wounds that usually lead to amputation and death.
Immune response is an important aspect of the anti-tumor effect produced by a CD40L- encoding oncolytic adenovirus Running title: Oncolytic adenovirus coding for CD40L Authors and affiliations

Title Immune response is an important aspect of the anti-tumor effect produced by a CD40Lencoding oncolytic adenovirus Running title: Oncolytic adenovirus coding for CD40L Authors and affiliations Iulia Diaconu, Vincenzo Cerullo, Mari LM Hirvinen, Sophie Escutenaire, Matteo Ugolini, Saila K Pesonen, Simona Bramante, Suvi Parviainen, Anna Kanerva, Angelica SI Loskog , Aristides G. Eliopoulos , Sari Pesonen*, Akseli Hemminki* Cancer Gene Therapy Group, Molecular Cancer Biology Program & Transplantation Laboratory & Haartman Institute & Finnish Institute for Molecular Medicine, University of Helsinki, 00290 Helsinki, Finland 2 Department of Obstetrics and Gynecology, HUCH, Helsinki, Finland Division of Clinical Immunology, Rudbeck Laboratory, Uppsala University, Uppsala, Sweden Laboratory of Molecular & Cellular Biology, University of Crete Medical School and Laboratory of Cancer Biology, Institute of Molecular Biology & Biotechnology, FORTH, Heraklion, Crete, Greece.
Estimating Semantic Similarity for Targeted Marketing based on Fuzzy Sets and the Odenet Ontology

—Estimating the semantic similarity between texts is of vital importance for a wide range of application scenarios in natural language processing. With the increasing availability of large text corpora, data-driven approaches like Word2Vec became quite successful. In contrast, semantic methods, which employ manually designed knowledge bases like ontologies lost some of their former popularity. However, manually designed knowledge can still be a valuable resource, since it can be leveraged to boost the performance of data-driven approaches. We introduce in this paper a novel hybrid similarity estimate based on fuzzy sets that exploits both word embeddings and a lexical ontology. As ontology we use Odenet, a freely available resource recently developed by the Darmstadt University of Applied Sciences. Our application scenario is targeted marketing, in which we aim to match people to the best ﬁtting marketing target group based on short German text snippets. The evaluation showed that the use of an ontology did indeed improve the overall result in comparison with a baseline data-driven estimate.
Modeling air pollution under uncertainty by using deep generative models

Modeling and forecasting ambient air pollution is a relevant problem because it is helpful for decision-makers and urban city planners to understand one of the main health problems in the urban area, the degradation of air quality due to motorized road mobility. This article addresses data-driven outdoor pollution modeling given limited data about road traﬃc density and pollution concentration. In order to deal with such a lack of data, we propose a deep generative model able to synthesize synthetic nitrogen dioxide concentration given road traﬃc density. Speciﬁcally, we train conditional generative adversarial networks. The experimental analysis indicates that the proposed approach generates accurate and diverse pollution data, while requiring reduced computational time.
Disruption of IAP/SHPS-1 association inhibits pathophysiologic changes in retinal endothelial function in diabetic rats

Aims— Our studies have shown that the association between integrin-associated protein (IAP) and SHPS-1 regulates the response of cells including osteoclasts, osteoblasts, smooth muscle and retinal endothelial cells to Insulin-like growth factor-I (IGF-I). The aims of this study were to determine whether the regulation of IGF-I responsiveness by IAP/SHPS-1 association is a generalized response of endothelial cells, to identify the mechanism by which IAP/SHPS-1 association contributes to changes in endothelial cell responses to IGF-I and to determine whether inhibiting their association alters pathophysiologic changes that occur in vivo. Methods and Results— Endothelial cells, maintained in 5mmol/l glucose, showed constitutive cleavage of the extracellular domain of IAP (containing the SHPS-1 binding site) and IAP/SHPS-1 association was not detected. In contrast, hyperglycemia inhibited IAP cleavage allowing IAP/ SHPS-1 association and IGF-I stimulated SHPS-1 tyrosine phosphorylation. Exposure to an anti-IAP antibody that disrupts IAP/SHPS-1 association inhibited IGF-I stimulated tube formation and increased permeability. Rodent models of endothelial cell dysfunction were used to investigate the role of IAP-SHPS-1 association in endothelial cell function in vivo. Basal IAP/SHPS-1 association was not detected in retinal extracts in normal rats but was fully restored in rats with diabetes. The anti-IAP antibody inhibited IAP/SHPS-1 association and reduced retinal vascular permeability and leukocyte adherence to levels that were similar to non-diabetic rats. The antibody also significantly inhibited aberrant neovascularization that was induced by hypoxia. Conclusions— Our results demonstrate that the increase in IAP/SHPS-1 association contributes to the pathophysiologic changes in the endothelium that are induced by hyperglycemia and hypoxia.
Reprovisioning for latency-aware dynamic service chaining in metro networks

To support newly emerging and highly dynamic 5G services, optical metro networks must be capable of provisioning services on the fly. Network function virtualization (NFV) is leveraged to fulfill these dynamic service demands by placing virtual network functions (VNFs) in NFV-capable network nodes and chaining them together (“service chaining”). In addition, new 5G service chains often have bandwidth requirements with subwavelength granularity, making traffic grooming essential for efficient network resource utilization. However, the latency requirement for these services will not allow one to always perform traffic grooming, as grooming operations add non-negligible latency to traffic, and this might lead to poor utilization and high service blocking. Thus, it is important to investigate dynamic solutions to increase network utilization and decrease service blocking. One approach to achieve this goal is to reprovision service chains (SCs) to use network resources as efficiently as possible. Reprovisioning consists of tearing down a service chain and reallocating its resources, typically with the intent to make room for new chains that would be otherwise rejected. While traditional reprovisioning entailed only routing reassignment, reprovisioning of SCs entails both rerouting traffic and/or relocating VNFs, hence originating new research problems. In this paper, we propose new heuristic algorithms to reprovision SCs whenever a service cannot be provisioned. We provide two different approaches to perform reprovisioning, i.e., bandwidth and location. While bandwidth reprovisioning consists of modifying only bandwidth assignment of SCs, location reprovisioning considers the possibility of changing the nodes each SC is mapped to. We also considered two different optical network architectures. Results obtained on realistic network topology and services show that location reprovisioning allows us to achieve up to 28% improvement in terms of the number of SCs we are able to provision in the network.
A Google Trends Approach to Identify Distinct Diurnal and Day-of-Week Web-Based Search Patterns Related to Conjunctivitis and Other Common Eye Conditions: Infodemiology Study

Background Studies suggest diurnal patterns of occurrence of some eye conditions. Leveraging new information sources such as web-based search data to learn more about such patterns could improve the understanding of patients’ eye-related conditions and well-being, better inform timing of clinical and remote eye care, and improve precision when targeting web-based public health campaigns toward underserved populations. Objective To investigate our hypothesis that the public is likely to consistently search about different ophthalmologic conditions at different hours of the day or days of week, we conducted an observational study using search data for terms related to ophthalmologic conditions such as conjunctivitis. We assessed whether search volumes reflected diurnal or day-of-week patterns and if those patterns were distinct from each other. Methods We designed a study to analyze and compare hourly search data for eye-related and control search terms, using time series regression models with trend and periodicity terms to remove outliers and then estimate diurnal effects. We planned a Google Trends setting, extracting data from 10 US states for the entire year of 2018. The exposure was internet search, and the participants were populations who searched through Google’s search engine using our chosen study terms. Our main outcome measures included cyclical hourly and day-of-week web-based search patterns. For statistical analyses, we considered P<. 001 to be statistically significant. Results Distinct diurnal (P<.001 for all search terms) and day-of-week search patterns for eye-related terms were observed but with differing peak time periods and cyclic strengths. Some diurnal patterns represented those reported from prior clinical studies. Of the eye-related terms, “pink eye” showed the largest diurnal amplitude-to-mean ratios. Stronger signal was restricted to and peaked in mornings, and amplitude was higher on weekdays. By contrast, “dry eyes” had a higher amplitude diurnal pattern on weekends, with stronger signal occurring over a broader evening-to-morning period and peaking in early morning. Conclusions The frequency of web-based searches for various eye conditions can show cyclic patterns according to time of the day or week. Further studies to understand the reasons for these variations may help supplement the current clinical understanding of ophthalmologic symptom presentation and improve the timeliness of patient messaging and care interventions.
P97/VCP ATPase inhibitors can rescue p97 mutation-linked motor neuron degeneration

Abstract Mutations in p97/VCP cause two motor neuron diseases: inclusion body myopathy associated with Paget disease of bone and frontotemporal dementia and familial amyotrophic lateral sclerosis. How p97 mutations lead to motor neuron degeneration is, however, unknown. Here we used patient-derived induced pluripotent stem cells to generate p97 mutant motor neurons. We reduced the genetic background variation by comparing mutant motor neurons to its isogenic wild type lines. Proteomic analysis reveals that p97R155H/+ motor neurons upregulate several cell cycle proteins at Day 14, but this effect diminishes by Day 20. Molecular changes linked to delayed cell cycle exit are observed in p97 mutant motor neurons. We also find that two p97 inhibitors, CB-5083 and NMS-873, restore some dysregulated protein levels. In addition, two p97 inhibitors and a food and drug administration-approved cyclin-dependent kinase 4/6 inhibitor, Abemaciclib, can rescue motor neuron death. Overall, we successfully used iPSC-derived motor neurons, identified dysregulated proteome and transcriptome and showed that p97 inhibitors rescue phenotypes in this disease model.
Speci¢city of catecholamine-induced growth in Escherichiacoli O157:H7,Salmonellaenterica and Yersiniaenterocolitica

The present study demonstrates that catecholamine responsiveness in Yersinia enterocolitica , a bacterial pathogen whose infectious spectrum is principally limited to the gut, is limited to norepinephrine and dopamine, and not epinephrine; this behavior contrasts with observations for two pathogens with a wider extra-gastrointestinal spectrum, Escherichia coli O157:H7 and Salmonella enterica, which respond to all three catecholamines. Epinephrine showed lower potency than norepinephrine and dopamine in inducing growth of E. coli and S. enterica , and was a potent antagonist of norepinephrine and dopamine growth responsiveness in Y. enterocolitica . Given that only norepinephrine and dopamine and not epinephrine-containing neurons are found with the enteric nervous system, the results suggest that certain of the more exclusive enteric pathogens may have developed response systems preferentially