Miracle-dz/UniFAR-FTUs huggingface dataset:
Cognitive Machine-to-Machine Communications for Internet-of-Things: A Protocol Stack Perspective

Machine-to-machine (M2M) communications enables networked devices to exchange information among each other as well as with business application servers and therefore creates what is known as the Internet-of-Things (IoT). The research community has a consensus for the need of a standardized protocol stack for M2M communications. On the other hand, cognitive radio technology is very promising for M2M communications due to a number of factors. It is expected that cognitive M2M communications will be indispensable in order to realize the vision of IoT. However cognitive M2M communications requires a cognitive radio-enabled protocol stack in addition to the fundamental requirements of energy efficiency, reliability, and Internet connectivity. The main objective of this paper is to provide the state of the art in cognitive M2M communications from a protocol stack perspective. This paper covers the emerging standardization efforts and the latest developments on protocols for cognitive M2M networks. In addition, this paper also presents the authors' recent work in this area, which includes a centralized cognitive medium access control (MAC) protocol, a distributed cognitive MAC protocol, and a specially designed routing protocol for cognitive M2M networks. These protocols explicitly account for the peculiarities of cognitive radio environments. Performance evaluation demonstrates that the proposed protocols not only ensure protection to the primary users (PUs) but also fulfil the utility requirements of the secondary M2M networks.
Safety and efficacy of adapalene 0.1% / benzoyl peroxide 2.5% in the long‐term treatment of predominantly moderate acne with or without concomitant medication – results from the non‐interventional cohort study ELANG

Acne is a chronic inflammatory disease requiring long‐term treatment. The fixed‐dose combination adapalene 0.1%/benzoyl peroxide 2.5% (adapalene‐BPO) is indicated for the once‐daily topical treatment of Acne vulgaris when comedones, papules and pustules are present.
Controlling narrative time in interactive storytelling

Narrative time has an important role to play in Interactive Storytelling (IS). The prevailing approach to controlling narrative time has been to use implicit models that allow only limited temporal reasoning about virtual agent behaviour. In contrast, this paper proposes the use of an explicit model of narrative time which provides a control mechanism that enhances narrative generation, orchestration of virtual agents and number of possibilities for the staging of agent actions. This approach can help address a number of problems experienced in IS systems both at the level of execution staging and at the level of narrative generation. Consequently it has a number of advantages: it is more flexible with respect to the staging of virtual agent actions; it reduces the possibility of timing problems in the coordination of virtual agents; and it enables more expressive representation of narrative worlds and narrative generative power. Overall it provides a uniform, consistent, principled and rigorous approach to the problem of time in agent-based storytelling. In the paper we demonstrate how this approach to controlling narrative time can be implemented within an IS system and illustrate this using our fully implemented IS system that features virtual agents inspired by Shakespeare's The Merchant of Venice. The paper presents results of an experimental evaluation with the system that demonstrates the use of this approach to co-ordinate the actions of virtual agents and to increase narrative generative power.
Ionic Current Basis of Electrocardiographic Waveforms: A Model Study

Body surface electrocardiograms and electrograms recorded from the surfaces of the heart are the basis for diagnosis and treatment of cardiac electrophysiological disorders and arrhythmias. Given recent advances in understanding the molecular mechanisms of arrhythmia, it is important to relate these electrocardiographic waveforms to cellular electrophysiological processes. This modeling study establishes the following principles: (1) voltage gradients created by heterogeneities of the slow-delayed rectifier (IKs) and transient outward (Ito) potassium current inscribe the T wave and J wave, respectively; T-wave polarity and width are strongly influenced by the degree of intercellular coupling through gap-junctions. (2) Changes in [K+]o modulate the T wave through their effect on the rapid-delayed rectifier, IKr. (3) Alterations of IKs, IKr, and INa (fast sodium current) in long-QT syndrome (LQT1, LQT2, and LQT3, respectively) are reflected in characteristic QT-interval and T-wave changes; LQT1 prolongs QT without widening the T wave. (4) Accelerated inactivation of INa on the background of large epicardial Ito results in ST elevation (Brugada phenotype) that reflects the degree of severity. (5) Activation of the ATP-sensitive potassium current, IK(ATP), is sufficient to cause ST elevation during acute ischemia. These principles provide a mechanistic cellular basis for interpretation of electrocardiographic waveforms.
Exploration, novelty, surprise, and free energy minimization

This paper reviews recent developments under the free energy principle that introduce a normative perspective on classical economic (utilitarian) decision-making based on (active) Bayesian inference. It has been suggested that the free energy principle precludes novelty and complexity, because it assumes that biological systems—like ourselves—try to minimize the long-term average of surprise to maintain their homeostasis. However, recent formulations show that minimizing surprise leads naturally to concepts such as exploration and novelty bonuses. In this approach, agents infer a policy that minimizes surprise by minimizing the difference (or relative entropy) between likely and desired outcomes, which involves both pursuing the goal-state that has the highest expected utility (often termed “exploitation”) and visiting a number of different goal-states (“exploration”). Crucially, the opportunity to visit new states increases the value of the current state. Casting decision-making problems within a variational framework, therefore, predicts that our behavior is governed by both the entropy and expected utility of future states. This dissolves any dialectic between minimizing surprise and exploration or novelty seeking.
A Digital Signal-based Prognostic Approach to Factory Automation

A data network from a control system is usually consist of complex wiring systems to communicate with manufacturing lines. The electrical connections by the wiring systems can be deteriorated by wire faults such as chafing in the wiring system. During the life cycle of the wiring system, field stress conditions such as mechanical stress condition often cause and intensify the wire faults. The progress of wire fault can cause other wire failures such as cutoff or arcing. Furthermore, failures in the connected wires may eventually cause malfunctions in facilities of manufacturing lines. In order to prevent serious failures, health of the wiring system can be monitored in real time to repair or replace the damaged wires before the time to failure. However, the conventional approaches to wire health monitoring often require additional connections to the wiring system due to additional monitoring devices. Thus, the operation of the facilities may be interfered when the monitoring devices monitor wires. As a result, the conventional approaches, which require additional devices, have difficulty detecting the extent of wire damages in real time, and may end up neglecting the progress of chafing. In this study, a method for wire health monitoring is developed to prevent wire failures by monitoring wiredamages in real time. Digital signal is affected adversely by impedance discontinuity on the transmission line. By monitoring the integrity of digital signal continuously, time to failure can be predicted in real time depending on the extent of wire damage. In addition, an accelerated wire abrasion test was designed to damage wires gradually. During the abrasion test, the integrity of the transmitted digital signal was continuously deteriorated. The monitored signal makes it possible to extrapolate the degradation pattern of the signal parameters depending on the extent of wire damage. Thus, the results in this study validate that the proposed method is capable of monitoring the wire damage to diagnose a wiring system with real-time information.
THE USE OF AI APPLICATION FOR WRITING CV: DESCRIPTIVE ANALYSIS

Several research studies have proven how an Artificial Intelligence (AI) application eases people's jobs in writing. In this regard, AI applications and how students use them in writing Curriculum Vitae (CV) were described. Eighty business students participated in answering the online questionnaire. The result shows that instead of using AI-based-CV Maker instantly, the participants prefer AI assistance for technical skills such as translation, design and grammar checking. AI tools are only one of the tools to use due to trust issues on content and contextual background.
Preserving Video Quality in IPTV Networks

Growing numbers of service providers are implementing video services over IP networks, and discovering the unique challenges of providing a high quality-of-experience (QoE) to subscribers. Delivering consistent QoE in packet-switched networks can be a complex proposition due to the high sensitivity of video traffic to packet loss, as well as to delay and jitter. Preserving video quality in IP Television (IPTV) networks that mostly rely on copper access lines poses an even greater challenge. Service providers need intelligent mechanisms in core and distribution networks to prevent congestion that deteriorates video quality, as well as intelligence between the aggregation networks and IP set-top box (STB) to repair packet losses, speed up channel change times and monitor the quality of the subscriber experience. This paper discusses a series of core and aggregation-layer approaches, collectively referred to as Visual Quality of Experience (VQE) to address these issues. The VQE approach encompasses on-path video connection admission control (CAC) employing Resource ReSerVation Protocol (RSVP) in the core and aggregation layers, and a real-time signaling mechanism operating between the provider aggregation edge and the IP STBs to address packet losses, long channel change times and quality monitoring.
Assessment of Noninvasive Risk Markers of Subclinical Atherosclerosis in Premenopausal Women with Previous History of Gestational Diabetes Mellitus

Introduction: Gestational diabetes mellitus (GDM) is state of carbohydrate intolerance detected first time during pregnancy. GDM represents a significant risk factor for the development of CVD in women. The degree to which women with histories of gestational diabetes are at risk for cardiovascular disease, beyond their predisposition to future diabetes, is still unclear. The aim of our study was to assess the presence of surrogate markers of subclinical atherosclerosis which can be present in them even without developing type 2 diabetes. Subjects and Methods: In this descriptive cross-sectional hospital based study, 50 patients 20-45 yrs of age, premenopausal, at least 1 yr past her most recent pregnancy, and not more than 5 yr past her index pregnancy with GDM. These patients and controls who did not have GDM were assessed for carotid intima media thickness,endothelial dysfunction, epicardial fat thickness and other cardiovascular risk factors. Results: Women with pGDM were found to have unfavourable cardiovascular risk parameters. They also demonstrated more frequent occurrence of metabolic syndrome(64% vs 10%) than control subjects. Individual components of MS increased with increasing BMI in both the groups. As far as markers of subclinical atherosclerosis were concerned women with pGDM had significantly higher CIMT, FMD and epicardial fat thickness than control group. Conclusion: Women with pGDM, even before development of diabetes have significant differences in CVD risk factors when compared to those who do not have such history. Postpartum screening for glucose intolerance and efforts to minimize modifiable cardiovascular risk factors, including hypertension, viscerall adiposity, and dyslipidemia should be the most effective measures for lowering of cardiovascular risk.
Geographic Variations of Racial/Ethnic Disparities in Cervical Cancer Mortality in Texas

Objectives To examine how racial/ethnic disparities of cervical cancer mortality vary geographically and to identify factors contributing to the variation. Methods Using the population-weighted risk difference, the authors investigated geographic patterns of racial/ethnic disparities in cervical cancer mortality in Texas based on data from 1995 to 2008 georeferenced at the census tract level. In addition, we considered the impact of seven factors—stage at diagnosis, spatial access to health care, and five factors that were created from available demographic data: socioeconomic status (SES), the sociodemographic factor, the percentage of African Americans, the health insurance factor, and the behavioral factor—on racial/ethnic disparities in the analysis using multivariate logistic regression. Results SES, the sociodemographic factor, the percentage of African Americans, and racial/ethnic disparities in late-stage diagnosis in a census tract were independent predictors of a census tract’s displaying significant racial/ethnic disparities in cervical cancer mortality. Compared with a census tract with the highest SES, a census tract with the lowest SES was more likely to have higher mortality rates in African Americans (odds ratio 4.19, confidence interval 2.18–8.07) or Hispanics (odds ratio 8.15, confidence interval 5.27–12.61) than non-Hispanic whites after adjusting for covariates. Health insurance expenditures also influenced racial/ethnic disparities in mortality, although this effect was attenuated after adjusting for covariates. Neither our calculated behavioral factor nor spatial analysis of access to health care explained racial/ethnic gaps in mortality. Conclusions Findings from this study could allow cervical cancer intervention programs to more clearly identify areas that would reduce disparities in cervical cancer outcomes.
The WEKA machine learning workbench : Its application to a real world agricultural database

Numerous techniques have been proposed for learning rules and relationships from diverse data sets, in the hope that machines can help in the often tedious and error-prone process of knowledge acquisition. While these techniques are plausible and theoretically wellfounded, they stand or fall on their ability to make sense of real-world data. This paper describes a project that aims to apply a range of learning strategies to problems in primary industry, in particular agriculture and horticulture.
JASMONIC ACID LEVELS AND SEED DEVELOPMENT IN SUNFLOWER (HELIANTHUS ANNUUS L.)

Summary. Using gas–mass chromatography analyses (GS-MS) we have determined the endogenous levels of jasmonic acid (JA) in developing sunflower seeds. The level of JA was higher in the early phases of seed development. We have registered a maximum on day 5 after pollination. Spraying of plants with JA at the time of flowering induced marked changes in protein content. Five days after treatment total protein content decreased by 33% whereas 15 day after flowering it exceeded the control values by 33%. In addition, the results from the SDS-polyacrylamide gel eletrophoresis (SDSPAGE) revealed qualitative and quantitative changes in the spectra of soluble proteins.
The rabbit as an animal model in dental implant research

Dental implants that are integrated into the jaw bones are widely used to replace lost teeth in human beings. Tooth-loss is often related to loss of the surrounding alveolar bone. This can make implant placement difficult and a bone substituting material may be required. The standard method is to use a bone graft harvested from the patient which requires additional surgery than that needed for implant placement. Limitations in the amount of bone that can be harvested also pose a problem. In order to decrease the need for bone grafts, materials that can serve as substitutes and stimulate bone growth have been, and are being, developed. In this pilot study the research protocol for an in vivo experiment with a new calcium phosphate bone augmenting ceramic material, was evaluated. Two titanium screw type dental implants were placed in each tibial diaphysis of three, 12 month old, female New Zealand White rabbits. The implants where either surrounded by the experimental material, Straumann®BoneCeramic (positive control) or blood (negative control). For one week before as well as post-surgery the rabbits’ body weights were recorded daily. Each rabbit’s general condition, state of surgical wounds and the grade of limping was evaluated every day for as long as needed. Two weeks post-surgery an injection of a bone marker (calcein green) was planned. Three month post-surgery the rabbits were to be euthanized and the amount of newly formed bone evaluated with light microscopy. The osseointegration of the implants was to be measured histomorphometrically as the bone to implant contact in percent. However, the calcein green was never given and the bone formation and osseointegration never evaluated. All rabbits had to be euthanized within 24 days post-surgery because of fractures appearing in one or both tibia/e. Apart from the pilot study, the master thesis includes a literature review of dental implants, bone augmenting materials and how the rabbit can be used as an animal model in dental implant research.
Dynamical Clustering of Personalized Web Search Results

Most current search engines present the user a ranked list given the submitted user query. Top ranked search results generally cover few aspects of all search results. However, in many cases, the users are interested in the main themes of search results besides the ranked list so that the user will have a global view of search results. This goal is often achieved through clustering approaches. Personalized search studies ranking or reranking the search results based on implicit feedback. The personalized search system will infer user information need based on user search engine interaction and rerank the search results. Same as the ranked search result lists, clusterings of search results intuitively should also be dynamically tuned according to user search system interaction. Thus it brings interesting clustering challenges in the personalized search framework. Clustering results should change dynamically to reflect the personalized ranking of search results. However, traditional static clustering algorithms based on document similarity cannot achieve this goal. In this paper, We study how to incrementally cluster the search results and dynamically update the cluster representation based on user’s implicit feedback.
Optimization of Bark Fast Pyrolysis for the Production of Phenol-Rich Bio-oil

Bark is one of the most under-utilized types of lignocellulosic biomass in the forest industry. In this study, bark fast pyrolysis was optimized for phenols yield using response surface methodology (RSM), considering the pyrolysis temperature, gas flow rate, and biomass particle size. The bio-oil generated under optimal conditions was then characterized by gas chromatography-mass spectrometry (GC-MS), ultimate analysis, and several physical methods. A regression equation was estimated based on the statistical analysis. It was found that the optimal conditions for phenols yield were 485 °C (pyrolysis reaction temperature), 28 L/min (gas flow rate), and 0.35 mm (biomass particle size), giving an experimental phenols yield of 13.2 wt%. The bio-oil obtained in optimum conditions met ASTM standard D7544-12 and contained up to 30.42% phenols. This renewable, phenol-rich bio-oil may be a good feedstock for phenolic-based chemicals, such as phenolic resin and phenoplast.
Mortality Costs of and Policy Responses to the COVID-19 Pandemic in Côte d'Ivoire

The Policy Research Working Paper Series disseminates the findings of work in progress to encourage the exchange of ideas about development issues. An objective of the series is to get the findings out quickly, even if the presentations are less than fully polished. The papers carry the names of the authors and should be cited accordingly. The findings, interpretations, and conclusions expressed in this paper are entirely those of the authors. They do not necessarily represent the views of the International Bank for Reconstruction and Development/World Bank and its affiliated organizations, or those of the Executive Directors of the World Bank or the governments they represent.
Case Study "Beatles Songs" - What can be Learned from Unreliable Music Alignments?

As a result of massive digitization efforts and the world wide web, there is an exploding amount of available digital data describing and representing music at various semantic levels and in diverse formats. For example, in the case of the Beatles songs, there are numerous recordings including an increasing number of cover songs and arrangements as well as MIDI data and other symbolic music representations. The general goal of music synchronization is to align the multiple information sources related to a given piece of music. This becomes a difficult problem when the various representations reveal significant differences in structure and polyphony, while exhibiting various types of artifacts. In this paper, we address the issue of how music synchronization techniques are useful for automatically revealing critical passages with significant difference between the two versions to be aligned. Using the corpus of the Beatles songs as test bed, we analyze the kind of differences occurring in audio and MIDI versions available for the songs.
Joint VHR - LIDAR classification framework in urban areas using a priori knowledge and post processing shape optimization

In this paper we describe a joint methodology for exploiting multispectral and LIDAR data for the characterization of an urban area. The test site is the town of Uberlandia (Brazil). We first discuss the overall framework for 2D and 3D data fusion, and then introduce the approach investigated in this work. We then provide and discuss the mapping results obtained in our investigation. Finally, in order to increase the overall accuracy and enhance the extraction of single building/composite block shapes, a post-classification procedure is applied to the obtained map.