Miracle-dz/UniFAR-FTUs huggingface dataset:
Emotional Trace: Mapping of Facial Expression to Valence-arousal Space

This work was carried out in the context of a collaborative research project aiming at the exploration on new companion technology for cognitive technical systems (SFB-TRR 62). Author AAH designed the study, performed the statistical analysis, wrote the protocol, contributed to the experiments and wrote the first draft of the manuscript. Author AS contributed to the analysis of the study, to the literature searches and to the manuscript writing. Author RN participated in the experiments. Author SH contributed to the data gathering. Author HN managed the interpretation of the expressions’ intensity. All authors read and approved the final manuscript. ABSTRACT The automated analysis of facial expression is a long investigated subject in the computer vision community and has been boosted by applications in the field of human computer interaction (HCI). Besides mapping of facial expressions to basic emotion categories, what is often of limited use for HCI due to sparse occurrence of real emotions, other approaches have been proposed to transform facial expression to the two dimensional so-called valence arousal space. With these affective user state parameters available, the course of the interaction can basically be guided smarter, i.e. the computer can provide help to an apparently confused user. However, it has been shown that the valence arousal space transformation can be impaired due to inaccuracies in image based feature extraction. In this article we present an advanced method using image processing and 3-D computer vision technology that on the one hand suppresses this problem through hierarchical analysis. Further, our concept enables the assignment of an intensity level of the affective state, which can be a valuable parameter for the interaction. In this paper we give details on the system concept with the different processing steps and respective results. By the application of our method we achieve improvement of facial expression recognition compared to other state-of-the-art methods. In particular we can distinguish roughly 15 percent more classes while maintaining the high recognition rate.
Erase or Fill? Deep Joint Recurrent Rain Removal and Reconstruction in Videos

In this paper, we address the problem of video rain removal by constructing deep recurrent convolutional networks. We visit the rain removal case by considering rain occlusion regions, i.e. the light transmittance of rain streaks is low. Different from additive rain streaks, in such rain occlusion regions, the details of background images are completely lost. Therefore, we propose a hybrid rain model to depict both rain streaks and occlusions. With the wealth of temporal redundancy, we build a Joint Recurrent Rain Removal and Reconstruction Network (J4R-Net) that seamlessly integrates rain degradation classification, spatial texture appearances based rain removal and temporal coherence based background details reconstruction. The rain degradation classification provides a binary map that reveals whether a location is degraded by linear additive streaks or occlusions. With this side information, the gate of the recurrent unit learns to make a trade-off between rain streak removal and background details reconstruction. Extensive experiments on a series of synthetic and real videos with rain streaks verify the superiority of the proposed method over previous state-of-the-art methods.
Myolectric Response of the Upper Limbs to Temperature Variation

This article presents preliminary results of the effect of temperature variation in the environment on the human body at the myoelectric level, in order to be able to characterize it. The application of the results of this research aims to contribute in the future to the improvement of the prosthesis and therefore to the lifestyle of its users. The procedure used in the investigation required a temperaturecontrolled chamber, in which the right arm of the patient, who is exposed to these changes, is introduced. The information of the electromyographic signals (EMG) of the forearm was collected, as well as the temperatures of the body, Tb, chamber, Tc and environment Ta, for further analysis. The experiment was performed with ten patients who do not use any type of prosthesis. For the data adquisition, specialized electronic interfaces from several manufacturers and MATLAB & Simulink support software were used. The response of the EMG signal is shown in four different scenarios of the temperature variable: low steady state, increasing, high steady state and decreasing, effectively demonstrating changes of the EMG signal due to temperature variations.
TAXONOMICAL CLASSIFICATION : Ricinus communis Linn . Kingdom : Plantae-Plants Subkingdom : Tracheobionta-Vascular plants

Phytochemical and pharmacological investigation of anti-tubercular activity of the certain indigenous plants 36 2.1 PLANT PROFILE OF RICINUS COMMUNIS LINN. COMMON NAMES: Castor bean, Ricin, Castor oil plant, Palma christi, Wonder tree 2.1. 1 TAXONOMICAL CLASSIFICATION: Ricinus communis Linn. Kingdom: Plantae -Plants Subkingdom: Tracheobionta Vascular plants Superdivision: Spermatophyta Seed plants Division: Magnoliophyta Flowering plants Class: Magnoliopsida – Dicotyledons Subclass: Rosidae Order: Euphorbiales Family: Euphorbiaceae Spurge family Genus: Ricinus L. – Ricinus Species: Ricinus communis Linn. (1,2) . 2.1. 2 SYNONYMS: (3)
Inflammation and pain in skin and deep tissues

Ultraviolet-B irradiation model has been used for many years as a translational model since it is well known to induce cutaneous inflammatory pain in both animals and humans. The aim of this study project was to evaluate time course and sensory changes induced by UVB and in particular: 1) evaluate the change in sensitivity after inflammation inside and outside the irradiated skin, 2) investigate the existence of a mechanism of cumulative effects between cutaneous and deep-tissue hyperalgesia, 3) investigate the effect on mechanical hyperalgesia and allodynia induced by UVB irradiation after application of heat stimuli and sensitization of deep tissues.
Body Size: Body sizes in food chains of animal predators and parasites

Introduction Food chains in which animal predators are bigger than their animal prey are called predator chains; those in which the consumers are smaller are called parasite chains (Elton, 1927; Hutchinson, 1959, p. 147). The purpose of this chapter is to display and test empirically some consequences, for predator chains and parasite chains, of assuming that the average mass of a consumer species (predator or parasite) is related to the average mass of its animal resource species (prey or host) by a power law with an exponent less than 1. In 1858, as part of his development of the theory of evolution, Wallace (1858, p. 54) noted that animal predators are generally larger and less numerous than their prey. Among the many echoes of Wallace’s remark, Elton (1927) observed anecdotally that animal predators weigh more than their prey in terrestrial food chains, Hutchinson (1959) analyzed some of the theoretical consequences of predators weighing more than their prey, and Sheldon, Prakash and Sutcliffe (1972) and others posited that marine animal predators outweigh their marine animal prey (see also Humphries, this volume; Woodward & Warren, this volume). Only recently have body sizes been studied empirically in parasite chains (Memmott, Martinez & Cohen, 2000; Leaper & Huxham, 2002) and parasitoid chains (Cohen et al., 2005). The study of parasitoid chains (e.g. Rott & Godfray, 2000; Memmott et al., 2000) appears not to have been considered by Elton (1927) and Hutchinson (1959). Predator and parasite chains are not the only possibilities observed in nature. Other relations between mass and feeding arise from social hunting and metaphoetesis. Among animals that hunt socially (such as wolves and army ants), the aggregate mass of the hunting group may be a more appropriate index of size than the mass of an individual predator. In animals where mass or feeding habit or both change dramatically with the stage of the life cycle (as in many insects and fishes), it is misleading to represent the masses of all stages by a typical adult
pplicability of in vitro bioassays for the diagnosis of ivermectin esistance in Rhipicephalus microplus ( Acari : Ixodidae )

The applicability of laboratory bioassays to diagnose ivermectin (IVM) resistance in Rhipicephalus microplus was evaluated. Adult immersion tests (AITs), larval immersion tests (LITs) and larval packet tests (LPTs) were performed to characterise the effects of ivermectin toxicity on adults and larvae of a susceptible reference strain. The AIT was determined to be a reasonable assay but requires a large number of individuals to attain interpretable results. The LIT and LPT were validated with an IVM resistant strain, revealing resistance ratios (RRs) of 6.73 and 1.49, respectively. In a field survey, nine different populations of cattle tick from the states of São Paulo and Mato Grosso do Sul, Brazil, were analysed with iagnosis the LIT. Populations without previous exposure to ivermectin exhibited RRs between 0.87 and 1.01. Populations previously exposed to IVM showed RRs between 1.83 and 4.62. The LIT was more effective at discriminating between resistant and susceptible populations than the LPT. The use of the LIT is recommended for the diagnosis of ivermectin resistance in R. microplus.
RDF Data Analysis with Activation Patterns

RDF data can be analyzed with various query languages such as SPARQL or SeRQL. Due to their nature these query languages do not support fuzzy queries. In this paper we present a new method that transforms the information presented by subject-relation-object relations within RDF data into Activation Patterns. These patterns represent a common model that is the basis for a number of sophisticated analysis methods such as semantic relation analysis, semantic search queries, unsupervised clustering, supervised learning or anomaly detection. In this paper, we explain the Activation Patterns concept and apply it to an RDF representation of the well known CIA World Factbook.
Deterministic Timing for the Industrial Internet of Things

This paper is about reconciling the highly asynchronous untimed interactions that prevail on the Internet with time-sensitive operations of Things in the Internet of Things (IoT). Specifically, this paper addresses a design pattern that is widely used on the Internet called asynchronous atomic callbacks (AAC). We show that it is possible and practical to endow AACs with temporal semantics that can make system behaviors more repeatable and testable and can make the interactions between cyber services and physical Things safer. Our approach brings some of the key advantages of synchronous languages, specifically deterministic concurrency and logical synchrony. We show how a well-defined notion of logical time is compatible with AAC and can be used to endow applications with semantic notions of simultaneity, give them more control over the ordering of events, and enable the specification of real-time behaviors that nevertheless recognize the often long and highly variable latencies introduced in the Internet. We introduce labeled logical clock domains (LLCDs), which permit arbitrary mixtures of synchronized and unsynchronized behaviors and we show how LLCDs can be realized in the JavaScript language, which is widely used in Internet applications.
Baset Kid-Size 2014 Team Description Paper

This document introduces Baset Humanoid team for participating in Humanoid Kid-Size Robot League in Robocup 2014. Our humanoid kid-size team is mainly based on some of our team members previous developments and experiences in AUTMan 2013 [1] team which ranked second in RoboCup 2013 (Eindhoven, Netherland) and team Parand 2013 teen-size team which ranked 1 in Iranopen 2013. Our main research interests within the scope of the humanoid robots are robust realtime vision and object recognition, localization, navigation, and human interaction.
The Details That Matter: Frequency Resolution of Spectrograms in Acoustic Scene Classification

This study describes a convolutional neural network model submitted to the acoustic scene classification task of the DCASE 2017 challenge. The performance of this model is evaluated with different frequency resolutions of the input spectrogram showing that a higher number of mel bands improves accuracy with negligible impact on the learning time. Additionally, apart from the convolutional model focusing solely on the ambient characteristics of the audio scene, a proposed extension with pretrained event detectors shows potential for further exploration.
Sinking phytoplankton associated with carbon flux in the Atlantic Ocean

The composition of sinking particles and the mechanisms leading to their transport ultimately control how much carbon is naturally sequestered in the deep ocean by the “biological pump. ” While detrital particles often contain much of the sinking carbon, sinking of intact phytoplankton cells can also contribute to carbon export, which represents a direct flux of carbon from the atmosphere to the deep ocean by circumventing the surface ocean food web. Phytoplankton that contributed to carbon flux were identified in sinking material collected by short‐term sediment trap deployments conducted along a transect off the eastern shore of South America. Particulate organic carbon flux at 125 m depth did not change significantly along the transect. Instead, changes occurred in the composition and association of phytoplankton with detrital particles. The fluxes of diatoms, coccolithophores, dinoflagellates, and nano‐sized cells at 125 m were unrelated to the overlying surface population abundances, indicating that functional‐group specific transport mechanisms were variable across locations. The dominant export mechanism of phytoplankton at each station was putatively identified by principal component analysis and fell into one of three categories; (1) transport and sinking of individual, viable diatom cells, (2) transport by aggregates and fecal pellets, or (3) enhanced export of coccolithophores through direct settling and/or aggregation.
Clustering With Using Side Information

Side information is present along with many text mining application. This side information may be provenance information, any links in the document, web logs which containuser access behavior, the links for any document or any other non textual attributes which are embedded into the text document. All these attributes may contain a large amount of information for clustering purposes. But it is difficult to calculate the concerned importance of this side information especially when some of the data is noisy. In that situation, it is risky to merge side information into the mining process because it can enhance the quality of the representation for the mining process or can add noise in this system. Thus, there should be a proper way to do this mining process so that it will make use of side information to maximize their advantages. Therefore, it is recommended to design an efficient algorithm which makes combination of classical portioning algorithm with probabilistic models in order to create an effective clustering approach.
TR 18-017 Adaptive View Planning for Aerial 3 D Reconstruction

With the proliferation of small aerial vehicles, acquiring close up imagery for high quality reconstruction is gaining importance. We present an adaptive view planning method to collect such images in an automated fashion. We first start by sampling a small set of views to build a coarse proxy to the scene. We then present (i) a method that builds a set of adaptive viewing planes for efficient view selection and (ii) an algorithm to plan a trajectory that guarantees high reconstruction quality which does not deviates too much from the optimal one. The vehicle then follows the trajectory to cover the scene, and the procedure is repeated until reconstruction quality converges or a desired level of quality is achieved. The set of viewing planes provides an effective compromise between using the entire 3D free space and using a single view hemisphere to select the views. We compare our algorithm to existing methods in three challenging scenes. Our algorithm generates views which produce the least reconstruction error comparing to three different baseline approaches.
Mixed H-infinity and Passivity Analysis for Neural Networks with Mixed Time-Varying Delays via Feedback Control

The problem of mixed H∞ and passivity analysis for neural networks with mixed time-varying delays which consist of discrete and distributed time-varying delays via feedback control is investigated. Based on designing feedback controller and constructing a Lyapunov-Krasovskii functional (LKF) comprising novel integral terms, the neural networks system is exponentially stable satisfying mixed H∞ and passivity performance. Moreover, improved Jensen inequalities and convex combination idea are utilized to derive sufficient conditions in terms of linear matrix inequalities (LMIs). A numerical example is employed to demonstrate the effectiveness of the proposed method.
Soft Tissue Swelling Associated with the Use of rhBMP-2 in Long Bone Nonunions

Copyright © 2015 by Journal of Orthpaedic Case Reports Journal of Orthopaedic Case Reports | pISSN 2250-0685 | eISSN 2321-3817 | Available on www.jocr. co.in | doi:10.13107/jocr.2250-0685.297 This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/3.0) which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited. Dr. Andrew Young Dr. Adam Mirarchi Abstract Journal of Orthopaedic Case Reports 2015 July Sep: 5(3):Page 18-21 Case Report
Alzheimer ’ s Disease – A Complex Neurodegenerative Disorder with a Multifactorial Pathogenesis

Alzheimer’s disease (AD) is a complex and progressive neurodegenerative disorder resulting in continuous deterioration of cognition, daily living abilities and motor functions and consequently has a huge social and familial burden. To date, the drugs approved for AD treatment provide only modest symptomatic effects. At present, the combined therapy with memantine plus one cholinesterase inhibitor (ChEI) is the best option for the treatment of moderate-to-severe AD. This combination has demonstrated higher clinical efficacy than monotherapy with ChEIs, with similar safety and tolerability in several randomised-controlled clinical trials (RCTs). Recent long-term observational studies have shown that combination therapy slows the rate of cognitive and functional deterioration, delays the placement of patients in nursing homes and also provides evidence that it is more effective when initiated early. None of the drugs for AD tested in Phase III trials show evidence of disease modification. A few studies have shown that the newer drugs, particularly anti-amyloid and neurotrophic agents, may provide improved disease-modifying treatments of AD in the near future. Meanwhile, combination therapy with available drugs is the most effective AD treatment.
Trifolium mutabile as New Species of Annual Legume for Mediterranean Climate Zone: First Evidences on Forage Biomass, Nitrogen Fixation and Nutritional Characteristics of Different Accessions

The present study evaluated the forage production, nitrogen fixation and the qualitative characteristics of different accessions of Trifolium mutabile, a new species of annual clover, collected in southern Italy. Forage traits were assessed by harvesting plants at the vegetative stage (stem elongation) and the subsequent regrowth at the flowering stage (inflorescence emergence-main shoot). From results, significant differences were found among the accessions of T. mutabile in terms of forage biomass production (from 5.1 to 8.2 t ha−1 dry matter), capacity of nitrogen fixation (58.2–76.8% Ndfa) and forage nutritional characteristics. Besides the high forage yield, the investigated accessions showed favourable values of production and quality, representing also worthy germplasm for selection programs as well as the application for possible plant cultivar registration. Moreover, it is interesting to underline that T. mutabile may represent a valuable alternative to commonly cultivated annual clover species due to its prolonged vegetative cycle. However, further investigations are needed to assess the self-reseeding capacity of T. mutabile when utilized as pasture species.
Data Anonymization Approach for Data Privacy

Data Anonymization is one of the techniques for achieving the database privacy. In this method of data anonymization the facility of hiding the identification factor from the other users. Hence the feature of this method is used for the modification purpose only and that will remove the identities of person and appears table in same way. It will help for maintaining the risk factor. This approach can be increased data utility tradeoff in an organization. Scalability and privacy risk are the main factors regarding any database over an organization. Here this are two factor can be help to maximizing the data utility as well as minimizing the risk by using differential privacy preserving method. At the time of released data differential privacy preserving mechanism support for individual data hiding , by adding the noise and disclose for the secondary purpose.
MyoSpat: A system for manipulating sound and light through hand gestures

MyoSpat is an interactive audio-visual system that aims to augment musical performances by empowering musicians and allowing them to directly manipulate sound and light through hand gestures. We present the second iteration of the system that draws from the research findings to emerge from an evaluation of the first system [1]. MyoSpat 2 is designed and developed using the Myo gesture control armband as input device and Pure Data as gesture recognition and audio-visual engine. The system is informed by human-computer interaction (HCI) principles: tangible computing and embodied, sonic and music interaction design (MiXD). This paper reports a description of the system and its audio-visual feedback design. We present an evaluation of the system, its potential use in different multi-media contexts and in exploring embodied, sonic and music interaction principles
IFI-TB-2013-02 D REBIN : Efficient and Explainable Detection of Android Malware in Your Pocket

Malicious applications pose a threat to the security of the Android platform. The growing amount and diversity of these applications render conventional defenses largely ineffective and thus Android smartphones often remain unprotected from novel malware. In this paper, we propose DREBIN, a lightweight method for detection of Android malware that enables identifying malicious applications directly on the smartphone. As the limited resources impede monitoring applications at run-time, DREBIN performs a broad static analysis, gathering as many features of an application as possible. These features are embedded in a joint vector space, such that typical patterns indicative for malware can be automatically identified and used for explaining the decisions of our method. In an evaluation with 123,453 applications and 5,560 malware samples DREBIN outperforms several related approaches and detects 94% of the malware with few false alarms, where the explanations provided for each detection reveal relevant properties of the detected malware. On five popular smartphones, the method requires 10 seconds for an analysis on average, rendering it suitable for checking downloaded applications directly on the device.