Miracle-dz/UniFAR-FTUs huggingface dataset:
Towards Enhanced Usability of IT Security Mechanisms - How to Design Usable IT Security Mechanisms Using the Example of Email Encryption

Nowadays, advanced security mechanisms exist to protect data, systems, and networks. Most of these mechanisms are effective, and security experts can handle them to achieve a sufficient level of security for any given system. However, most of these systems have not been designed with focus on good usability for the average end user. Today, the average end user often struggles with understanding and using security mecha-nisms. Other security mechanisms are simply annoying for end users. As the overall security of any system is only as strong as the weakest link in this system, bad usability of IT security mechanisms may result in operating errors, resulting in inse-cure systems. Buying decisions of end users may be affected by the usability of security mechanisms. Hence, software provid-ers may decide to better have no security mechanism then one with a bad usability. Usability of IT security mechanisms is one of the most underestimated properties of applications and sys-tems. Even IT security itself is often only an afterthought. Hence, usability of security mechanisms is often the after-thought of an afterthought. This paper presents some guide-lines that should help software developers to improve end user usability of security-related mechanisms, and analyzes com-mon applications based on these guidelines. Based on these guidelines, the usability of email encryption is analyzed and an email encryption solution with increased usability is presented. The approach is based on an automated key and trust man-agement. The compliance of the proposed email encryption solution with the presented guidelines for usable security mechanisms is evaluated.
Performance Analysis of Cache Enabled Wireless NOMA Ultra Dense Networks Using PPP

Edge caching has become a popular technology to reduce backhaul congestion by caching the content at the local base station. This paper analyses the performance of cache-enabled wireless ultra-dense networks (UDN) networks, where non-orthogonal multiple access (NOMA) is utilized in the downlink for content delivery using stochastic geometric approach. Assuming a fixed delay in the backhaul links, the cumulative density function (CDF) of the cache delivery is derived rigorously. Simulation results for two typical NOMA users with given transmit power levels show improved performance. It can be seen that owing to the requirements of the signal-to-interference-and-noise ratio (SINR) for successive interference cancellation, both users achieve similar CDF for the delivery delay, and it is shown to vary with the delay threshold and the density of the base stations.
A Seven-Level Single-Phase Shared Leg Toroidal Transformer Based Inverter For Grid-Connected Applications

The present paper introduces a 7-level single-phase shared leg toroidal transformer-based inverter for grid-connected applications. It uses optimal device count compared to conventional topologies such as a single DC source, eight semiconductor switches, and three toroidal transformers to get a seven-level symmetrical output voltage. Besides, the selective harmonic elimination (SHE) technique demands solving the transcendental equations, hence it becomes difficult for real-time closed-loop operation when connected to the grid. However, these transcendental equations are converted to a closed-loop control system with reduced memory size and get switching angles to achieve precise control to eliminate the required harmonics. The proposed configuration is verified using MATLAB/SIMULINK software and validated through a real-time simulator (OPAL-RT).
Automatic structures: richness and limitations

This paper studies the existence of automatic presentations for various algebraic structures. The automatic Boolean algebras are characterised, and it is proven that the free Abelian group of infinite rank and many Fraisse limits do not have automatic presentations. In particular, the countably infinite random graph and the universal partial order do not have automatic presentations. Furthermore, no infinite integral domain is automatic. The second topic of the paper is the isomorphism problem. We prove that the complexity of the isomorphism problem for the class of all automatic structures is /spl Sigma//sub 1//sup 1/-complete.
DESIGNING MONETARY AND FISCAL POLICY RULES IN A NEW KEYNESIAN MODEL WITH RULE-OF-THUMB CONSUMERS

This paper studies the determinacy properties of monetary and fiscal policy rules in a small-scale New Keynesian model. We modify the standard model in two ways. First, we allow positive public debt in the steady state as in Leeper [Journal of Monetary Economics 27, 129–147 (1991)]. Second, we add rule-of-thumb consumers as in Bilbiie [Journal of Economic Theory 140, 162–196 (2008)]. Leeper studied a model in which Ricardian equivalence holds, and he showed that monetary and fiscal policy can be studied independently. In Bilbiie's analysis, rule-of-thumb consumers break the Ricardian equivalence and generate important consequences for the design of monetary policy. In his model, steady-state public debt was equal to zero. We study a model with both rule-of-thumb consumers and positive steady-state public debt. We find that the mix of fiscal and monetary policies that guarantees equilibrium determinacy is sensitive to the exact values of the parameters of the model.
Immunotherapy of a chemically-induced sarcoma in rats: characterization of the effector T cell subset and nature of suppression.

Chemically-induced sarcomas (BC5), established subcutaneously and growing progressively in BN rats, were completely eliminated by i.v. infusion of syngeneic effector cells. The effector cells were generated from BN spleen cells immune to BC5 in a mixed lymphocyte-tumor cell culture (MLTC). Generation of a high yield of effector cells that were efficacious in eliminating BC5 in vivo necessitated: depletion of macrophages from immune spleen populations, before preparation of MLTC; addition back to MLTC of a small number of macrophages from normal spleens to attain a level of 0.5% of the spleen cells in culture; and addition of T cell growth factor on day 5 of MLTC. With these conditions a subset of T cells was expanded. They were blast cells with surface markers W3/25 and Ia, which exhibited no cytotoxic activity in vitro, and probably functioned as a helper or amplifier element in the tumor-bearing host. Effector cells generated in MLTC with BC5, treated with mitomycin C, were specific for BC5 in vivo and did not affect growth of a viral-induced BN tumor.
Breast Cancer Diagnosis by using k-Nearest Neighbor with Different Distances and Classification Rules

Cancer diagnosis is one of the most studied problems in the medical domain. Several researchers have focused in order to improve performance and achieve to obtain satisfactory results. Breast cancer is one of cancer killer in the world. The diagnosis of this cancer is a big problem in cancer diagnosis researches. In artificial intelligent, machine learning is a discipline which allows to the machine to evolve through a process. Machine learning is widely used in bio informatics and particularly in breast cancer diagnosis. One of the most popular methods is K-nearest neighbors (K-NN) which is a supervised learning method. Using the K-NN in medical diagnosis is very interesting. The quality of the results depends largely on the distance and the value of the parameter “k” which represent the number of the nearest neighbors. In this paper, we study and evaluate the performance of different distances that can be used in the K-NN algorithm. Also, we analyze this distance by using different values of the parameter “k” and by using several rules of classification (the rule used to decide how to classify a sample). Our work will be performed on the WBCD database (Wisconsin Breast Cancer Database) obtained by the university of Wisconsin Hospital.
Midkine, a heparin-binding cytokine with multiple roles in development, repair and diseases

Midkine is a heparin-binding cytokine or a growth factor with a molecular weight of 13 kDa. Midkine binds to oversulfated structures in heparan sulfate and chondroitin sulfate. The midkine receptor is a molecular complex containing proteoglycans. Midkine promotes migration, survival and other activities of target cells. Midkine has about 50% sequence identity with pleiotrophin. Mice deficient in both factors exhibit severe abnormalities including female infertility. In adults, midkine is expressed in damaged tissues and involved in the reparative process. It is also involved in inflammatory reactions by promoting the migration of leukocytes, induction of chemokines and suppression of regulatory T cells. Midkine is expressed in a variety of malignant tumors and promotes their growth and invasion. Midkine appears to be helpful for the treatment of injuries in the heart, brain, spinal cord and retina. Midkine inhibitors are expected to be effective in the treatment of malignancies, rheumatoid arthritis, multiple sclerosis, renal diseases, restenosis, hypertension and adhesion after surgery.
Vivir la territorialidad: Turismo mapuche y desarrollo

This article examines how Mapuche entrepreneurs are shaping the landscape of tourism in southern Chile in the context of indigenous development. Based on ethnographic research in and around Lican Ray, we looked at the impacts of Mapuche tourism ventures on development and deterritorialisation. Furthermore, we consider Mapuche tourism as a strategy of resistance in response to the deepening displacement of Mapuche population and the loss of traditional cultural values. The first section means to give an overview of the complexity of issues regarding (indigenous) tourism and development as well as to introduce Mapuche tourism practices. Next, dealing with notions as territoriality and collectivism, we argue that Mapuche entrepreneurs are reappropriating Mapuche culture for development. Mapuche tourism is mobilising alternative ways for development, being and relating to the profound relationship they have with their territory and environment in accordance to their worldview. Finally, following the theories of anthropologists Charles Hale and James Scott, we show how Mapuche tourism is shaped in globalisation through Chile’s neoliberal policy. However, the Mapuche indigenous people active in tourism demonstrate that they possess the agency to construct strategies of ‘cultural resistance’. This article brings new perspectives to the study of indigenous tourism and development and represents Mapuche tourism as an opportunity for both indigenous development and resistance.
Chronic Critical Illness in Infants and Children: A Speculative Synthesis on Adapting ICU Care to Meet the Needs of Long-Stay Patients

Objectives: In this review, we examine features of ICU systems and ICU clinician training that can undermine continuity of communication and longitudinal guidance for decision making for chronically critically ill infants and children. Drawing upon a conceptual model of the dynamic interactions between patients, families, clinicians, and ICU systems, we propose strategies to promote longitudinal decision making and improve communication for infants and children with prolonged ICU stays. Data Sources: We searched MEDLINE and PubMed from inception to September 2015 for English-language articles relevant to chronic critical illness, particularly of pediatric patients. We also reviewed bibliographies of relevant studies to broaden our search. Study Selection: Two authors (physicians with experience in pediatric neonatology, critical care, and palliative care) made the final selections. Data Extraction: We critically reviewed the existing data and models of care to identify strategies for improving ICU care of chronically critically ill children. Data Synthesis: Utilizing the available data and personal experience, we addressed concerns related to family perspectives, ICU processes, and issues with ICU training that shape longitudinal decision making. Conclusions: As the number of chronically critically ill infants and children increases, specific communication and decision-making models targeted at this population could improve the feedback between acute, daily ICU decisions and the patient’s overall goals of care. Adaptations to ICU systems of care and ICU clinician training will be essential components of this progress.
Tracking CO2 Plumes in Clay‐Rich Rock by Distributed Fiber Optic Strain Sensing (DFOSS): A Laboratory Demonstration

Monitoring the migration of pore pressure, deformation, and saturation plumes with effective tools is important for the storage and utilization of fluids in underground reservoirs, such as geological stores of carbon dioxide (CO2) and natural gas. Such tools would also verify the security of the fluid contained reservoir‐caprock system. Utilizing the swelling strain attributed to pressure buildup and the adsorption of supercritical CO2 on clay minerals, we tracked the fluid plume in a natural clay‐rich Tako sandstone at the laboratory core scale. The strain was measured by a high‐resolution distributed fiber optic strain sensing (DFOSS) tool. The strain changes induced by CO2 adsorptions on clay minerals were significantly greater than those caused by pore pressure alone. The distribution of the swelling strain signals effectively captured the dynamic breakthrough of the CO2 plume from the high‐ to low‐permeability regions in the Tako sandstone. Besides revealing the in situ deformation state, the measured strain changes can track the movement of the CO2 plume as it enters the clay‐rich critical regions in the reservoir‐caprock system. The present findings and potential future applications of DFOSS in the field are expected to enhance the monitoring and management of underground fluid reservoirs.
Identifying the Subject of Documents in Digital Libraries Automatically Using Frequently Occurring Words - Study and Findings

Contemporary information databases contain millions of electronic documents. The immense number of documents makes it difficult to conduct efficient searches on the Internet. Several studies have found that associating documents with a subject or list of topics can make them easier to locate online [5] [6] [7]. Effective cataloging of information is performed manually, requiring extensive resources. Consequently, at present most information is not cataloged. This paper will present the findings of a study based on a software tool (TextAnalysis) that automatically identifies the subject of a document. We tested documents in two subject categories: geography and family studies. The present study follows an earlier one that examined the subject categories of industrial management and general management.
A Novel Statistical Algorithm for Gene Expression Analysis Helps Differentiate Pregnane X Receptor-Dependent and Independent Mechanisms of Toxicity

Genome-wide gene expression profiling has become standard for assessing potential liabilities as well as for elucidating mechanisms of toxicity of drug candidates under development. Analysis of microarray data is often challenging due to the lack of a statistical model that is amenable to biological variation in a small number of samples. Here we present a novel non-parametric algorithm that requires minimal assumptions about the data distribution. Our method for determining differential expression consists of two steps: 1) We apply a nominal threshold on fold change and platform p-value to designate whether a gene is differentially expressed in each treated and control sample relative to the averaged control pool, and 2) We compared the number of samples satisfying criteria in step 1 between the treated and control groups to estimate the statistical significance based on a null distribution established by sample permutations. The method captures group effect without being too sensitive to anomalies as it allows tolerance for potential non-responders in the treatment group and outliers in the control group. Performance and results of this method were compared with the Significant Analysis of Microarrays (SAM) method. These two methods were applied to investigate hepatic transcriptional responses of wild-type (PXR+/+) and pregnane X receptor-knockout (PXR−/−) mice after 96 h exposure to CMP013, an inhibitor of β-secretase (β-site of amyloid precursor protein cleaving enzyme 1 or BACE1). Our results showed that CMP013 led to transcriptional changes in hallmark PXR-regulated genes and induced a cascade of gene expression changes that explained the hepatomegaly observed only in PXR+/+ animals. Comparison of concordant expression changes between PXR+/+ and PXR−/− mice also suggested a PXR-independent association between CMP013 and perturbations to cellular stress, lipid metabolism, and biliary transport.
Mild cognitive impairment

Mild cognitive impairment (MCI) is a controversial label for forms of age-related, intellectual difficulties unassociated with impairments in activities of daily living. The principal issue is whether this arbitrary, heterogeneous and unreliable term is appropriate to use clinically. Persons with the label MCI may progress to different types of dementia, stay stable, or even improve. In this article we offer a philosophical analysis of MCI from epistemological, ethical and semantic perspectives. We believe that the term should currently not be used clinically.
Disentanglement-Guided Spatial-Temporal Graph Neural Network for Metro Flow Forecasting (Student Abstract)

In recent intelligent transportation applications, metro flow forecasting has received much attention from researchers. Most prior arts endeavor to explore spatial or temporal dependencies while ignoring the key characteristic patterns underlying historical flows, e.g., trend and periodicity. Although the multiple granularity distillations or spatial dependency correlation can promote the flow estimation. However, the potential noise and spatial dynamics are under-explored. To this end, we propose a novel Disentanglement-Guided Spatial-Temporal Graph Neural Network or DGST to address the above concerns. It contains a Disentanglement Pre-training procedure for characteristic pattern disentanglement learning, a Characteristic Pattern Prediction for different future characteristic explorations, and a Spatial-Temporal Correlation for spatial-temporal dynamic learning. Experiments on a real-world dataset demonstrate the superiority of our DGST.
Multi-Scale Feature Fusion Network for Lip Recognition

Visual speech recognition (VSR) is also known as lip recognition. Recently, it has been widely explored due to the development of deep learning. Lip recognition is a discrimination issue, where the information provided by the delicate movement of the lips is most remarkable of all. This places a higher demand on the model's ability to extract features of minor variation around the lips. In this paper, a three-dimensional convolutional network (3D CNN) multi-branch feature fusion network is proposed for extracting spatiotemporal featuresof continuous images. The features of multi-branch feature fusion network are utilized to fully extract partial and general characteristics from sequential imagery and further enhance the feature information to deliver more accurate function info to the back-end classification network. The excellence of quite a few methods requires the support of huge volume of data, and in favor of test the effect of small-scale data sets. This experimentis conducted using the Oulu Vs2dataset to obtain exciting experimental results. After 20 iterations of the experiment, the maximum accuracy absolutely improves by 0.8% and the average accuracy improves by 1%.
The Neural Basis of Altruistic Punishment

Many people voluntarily incur costs to punish violations of social norms. Evolutionary models and empirical evidence indicate that such altruistic punishment has been a decisive force in the evolution of human cooperation. We used H2 15O positron emission tomography to examine the neural basis for altruistic punishment of defectors in an economic exchange. Subjects could punish defection either symbolically or effectively. Symbolic punishment did not reduce the defector's economic payoff, whereas effective punishment did reduce the payoff. We scanned the subjects' brains while they learned about the defector's abuse of trust and determined the punishment. Effective punishment, as compared with symbolic punishment, activated the dorsal striatum, which has been implicated in the processing of rewards that accrue as a result of goal-directed actions. Moreover, subjects with stronger activations in the dorsal striatum were willing to incur greater costs in order to punish. Our findings support the hypothesis that people derive satisfaction from punishing norm violations and that the activation in the dorsal striatum reflects the anticipated satisfaction from punishing defectors.
A rate-based prefiltering approach to blast acceleration

DNA sequence comparison and database search have evolved in the last years as a field of strong competition between several reconfigurable hardware computing groups. In this paper we present a BLAST preprocessor that efficiently marks the parts of the database that may produce matches. Our prefiltering approach offers significant reduction in the size of the database that needs to be fully processed by BLAST, with a corresponding reduction in the run-time of the algorithm. We have implemented our architecture, evaluated its effectiveness for a variety of databases and queries, and compared its accuracy against the original NCBI Blast implementation. We have found that prefiltering offers at least a factor of 5 and up to 3 orders of magnitude reduction in the database space that needs to be fully searched. Due to its prefiltering nature, our approach can be combined with all major reconfigurable acceleration architectures that have been presented up to date.