Miracle-dz/UniFAR-FTUs huggingface dataset:
Fir-spruce and lime-fir-spruce forests of Vyatka-Kama biome

During the preparation of map “Biomes of Russia” in broadleaved-coniferous forests belt of the Eastern Europ Vyatka-Kama biome was substantiated. This territory is allocated for the first time at such a high level. Formations of fir-spruce and lime-fir-spruce forests occupy a central position in the vegetation cover of the biome and largely determine its specificity. As the result of ecological-morphological classification 7 groups of associations and 17 associations of vegetation have been determined.
Storm type effects on super Clausius–Clapeyron scaling of intense rainstorm properties with air temperature

Extreme precipitation is thought to increase with warming at rates similar to or greater than the water vapour holding capacity of the air at ~ 7% °C −1 , the so-called Clausius–Clapeyron (CC) rate. We present an empirical study of the variability in the rates of increase in precipitation intensity with air temperature using 30 years of 10 min and 1 h data from 59 stations in Switzerland. The analysis is conducted on storm events rather than fixed interval data, and divided into storm type subsets based on the presence of lightning which is expected to indicate convection. The average rates of increase in extremes (95th percentile) of mean event intensity computed from 10 min data are 6.5% °C −1 (no-lightning events), 8.9% °C −1 (lightning events) and 10.7% °C −1 (all events combined). For peak 10 min intensities during an event the rates are 6.9% °C −1 (no-lightning events), 9.3% °C −1 (lightning events) and 13.0% °C −1 (all events combined). Mixing of the two storm types exaggerates the relations to air temperature. Doubled CC rates reported by other studies are an exception in our data set, even in convective rain. The large spatial variability in scaling rates across Switzerland suggests that both local (orographic) and regional effects limit moisture supply and availability in Alpine environments, especially in mountain valleys. The estimated number of convective events has increased across Switzerland in the last 30 years, with 30% of the stations showing statistically significant changes. The changes in intense convective storms with higher temperatures may be relevant for hydrological risk connected with those events in the future.
Contribution to a bio-optical model for remote sensing of Lena River water

Bio-optical measurements and sampling were carried out in the delta of the Lena River (northern Siberia, Russia) between 26 June and 4 July 2011. The aim of this study was to determine the inherent optical properties of the Lena water, i.e., absorption, attenuation, and scattering coefficients, during the period of maximum runoff. This aimed to contribute to the development of a bio-optical model for use as the basis for optical remote sensing of coastal water of the Arctic. In this context the absorption by CDOM (colored dissolved organic matter) and particles, and the concentrations of total suspended matter, phytoplankton-pigments, and carbon were measured. CDOM was found to be the most dominant parameter affecting the optical properties of the river, with an absorption coefficient of 4.5–5 m −1 at 442 nm, which was almost four times higher than total particle absorption values at visible wavelength range. The wavelenght-dependence of absorption of the different water constituents was chracterized by determining the semi logarithmic spectral slope. Mean CDOM, and detritus slopes were 0.0149 nm −1 (standard deviation (stdev) = 0.0003, n = 18), and 0.0057 nm −1 (stdev = 0.0017, n = 19), respectively, values which are typical for water bodies with high concentrations of dissolved and particulate carbon. Mean chlorophyll a and total suspended matter were 1.8 mg m −3 (stdev = 0.734 n = 18) and 31.9 g m −3 (stdev = 19.94, n = 27), respectively. DOC (dissolved organic carbon) was in the range 8–10 g m −3 and the total particulate carbon (PC) in the range 0.25–1.5 g m −3 . The light penetration depth (Secchi disc depth) was in the range 30–90 cm and was highly correlated with the suspended matter concentration. The period of maximum river runoff in June was chosen to obtain bio-optical data when maximum water constituents are transported into the Laptev Sea. However, we are aware that more data from other seasons and other years need to be collected to establish a general bio-optical model of the Lena water and conclusively characterize the light climate with respect to primary production.
Musical ensemble performance : A theoretical framework and empirical findings on interpersonal coordination

Musical ensemble performance requires precise yet flexible interpersonal coordination. The former Max Planck Research Group on Music Cognition and Action investigated the psychological processes and brain mechanisms that enable such coordination. This paper provides an overview of the group’s research on factors that determine the quality of ensemble cohesion. First, the theoretical framework and empirical approach that guided our work are outlined, and then key findings are described. These findings address the role of individual differences in cognitive-motor ensemble skills (anticipation, attention, and adaptation), social-psychological factors (personality), and the performer’s knowledge about the music and familiarity with co-performers. The paper ends with a discussion of the implications of our research for pedagogical practice aimed at fostering excellence as an ensemble musician.
Influence of Storage Bin Design and Feed Characteristics on Flowability of Pig Diets Containing Maize Distillers Dried Grains with Solubles

Maize dried distillers grains with solubles (DDGS) is a valuable ingredient in the swine industry but when incorporated into diets at high levels (40%) poor flowability of the feed often results. Researchers have investigated the physical properties of DDGS and use of anti-caking agents to determine their influence on flowability but few studies have evaluated effects of feed storage structures on flowability. Thus, two experiments were designed to evaluate the effects of feed bin design and passive agitator use on flowability of a commercial swine finishing diet containing 40% DDGS. Six bins of three different designs were used, which included: a galvanized steel, seamless bin with a 60° cone (Steel60; Dealers Livestock, Glenwood, Minn.); a galvanized, corrugated steel bin with a 67° cone (Steel67; PigTek, Milford, Ind.); and a white, polyethylene bin with a 60° cone (Poly60; Prairie Pride, Winnipeg, MB). In Experiment 1, rate of feed flow from each bin was assessed on days 3, 7, and 21 post-feed delivery. Feed flow from Poly60 (736.8 kg/min) was faster than Steel60 (602.9 kg/min), with Steel67 having intermediate flow (663.3 kg/min). In Experiment 2, passive feed flow agitators (Sure Flo Agitator, Farmer Boy Ag Supply, Myerstown, Pa.) were installed in one bin of each design. Feed flow was evaluated on days 2, 3, 6, 7, 20, and 21 post-feed delivery. Feed flow from Poly60 (900.7 kg/min) was greater than flow from either Steel60 (826.7 kg/min) or Steel67 (843.8 kg/min). The passive agitator increased flow in Poly60 (970.0 vs. 831.4 kg/min), tended to improve feed flow in Steel67 (880.2 vs. 807.4 kg/min), but had no effect in Steel60 (826.8 vs. 826.7 kg/min). Results indicate feed bin design can influence flowability of feed containing 40% DDGS. Of the bins tested, the passive agitator appeared to improve feed flow in some, but not all bin designs.
MODELO DE AVALIAÇÃO DE ESTRATÉGIA AMBIENTAL ASSESSMENT MODEL FOR ENVIRONMENTAL STRATEGY

The goal of this study was to verify the model for assessing the environmental strategy Structure-Conduct-Performance SCP fi ts the textile segment. Based on the literature about environmental norms, we developed a qualitative research through a case study that sought to know the model for assessing the environmental strategy in an industry with specifi c characteristics of the textile sector. From the results analysis, questionnaires, documents and direct observation of the company modos operandi we can verify that the SCP model shows adherence to the practices of the company, also based on indicators defi ned in this model, the company demonstrated a strong environmental profi le, developing and integrating business strategies to the environmental context today’s competitive striving for sustainability, through respect for the environment and considering the available resources in the region, with strict targets and environmental controls.
Reply to the reviewers, December 16, 2014 “Geothermal evidence of the Late Pleistocene-Holocene orbital forcing (example from the Urals, Russia)” by D. Y. Demezhko and A. A. Gornostaeva

“Geothermal evidence of the Late Pleistocene-Holocene orbital forcing (example from the Urals, Russia)” by D. Y. Demezhko and A. A. Gornostaeva D. Y. Demezhko and A. A. Gornostaeva ddem54@inbox.ru Reply to the reviewers We are grateful to both J.-C. Mareschal and Anonymous Referee #2 for their positive response to our paper and helpful suggestions. We appreciate the constructive feedback. We have tried to answer your questions in detail and incorporate all of your suggestions into our revised paper. J.-C. Mareschal (Referee #1) One needs to go back to the first paper to see the original temperature profile data, which is unfortunate. We will include the figure with the original temperature-depth profile from borehole SG-4 in the revised paper (Fig 1).
Why Pain Is Still a Welfare Issue for Farm Animals, and How Facial Expression Could Be the Answer

Pain is a sensory and emotional experience that significantly affects animal welfare and has negative impacts on the economics of farming. Pain is often associated with common production diseases such as lameness and mastitis, as well as introduced to the animal through routine husbandry practices such as castration and tail docking. Farm animals are prey species which tend not to overtly express pain or weakness, making recognizing and evaluating pain incredibly difficult. Current methods of pain assessment do not provide information on what the animal is experiencing at that moment in time, only that its experience is having a long term negative impact on its behavior and biological functioning. Measures that provide reliable information about the animals’ affective state in that moment are urgently required; facial expression as a pain assessment tool has this ability. Automation of the detection and analysis of facial expression is currently in development, providing further incentive to use these methods in animal welfare assessment.
LEVANTAMENTO DA DIVERSIDADE DE FORMAS DE VIDA EM FLORESTA DE TERRA FIRME E DE VÁRZEA EM ESTÁGIO DE REGENERAÇÃO EM UMA PROPRIEDADE NO MUNICÍPIO DE CASTANHAL, PARÁ.

Introdução A Floresta Amazônica proporciona ao homem uma série de serviços ambientais, como a provisão de alimentos, a regulação climática, o controle de erosões e a ciclagem de nutrientes. A ausência desses serviços em decorrência do desmatamento descontrolado vem ocasionado consequências em escala global, dentre elas, a perda de biodiversidade e a elevação das temperaturas. As diferentes fitofisionomias são caracterizadas de acordo com o resultado do predomínio das formas vegetais com variadas formas de vida, dentre elas as ervas, arbustos e árvores (MARTINS & BATALHA, 2001). O conceito de fisionomia vegetal foi criado por Alexander von Humboldt, em 1805. Até aquela época, para os estudiosos não existia diferença entre flora e vegetação, sendo a mesma descrita por meio da lista de espécies que a constituíam, sendo que, a definição de plantas, vegetais e vegetação tinham o mesmo significado. Na região Bragantina do estado do Pará é comum a ocorrência de diferentes ecossistemas florestais com diferentes características em sua estrutura e estagio de sucessão, as quais variam normalmente quanto as características peculiares de cada ambiente, podendo
Deep Residual Network with Enhanced Upscaling Module for Super-Resolution

Single image super-resolution (SR) have recently shown great performance thanks to the advances in deep learning. In the middle of the deep networks for SR, a part that increases image resolution is required, for which a subpixel convolution layer is known as an efficient way. However, we argue that the method has room for improvement, and propose an enhanced upscaling module (EUM), which achieves improvement by utilizing nonlinear operations and skip connections. Employing our proposed EUM, we propose a novel deep residual network for SR, called EUSR. Our proposed EUSR was ranked in the 9th place among 24 teams in terms of SSIM in track 1 of the NTIRE 2018 SR Challenge [25]. In addition, we experimentally show that EUSR has comparable performance on ×2 and ×4 SR for four benchmark datasets to the state-of-the-art methods, and outperforms them on a large scaling factor (x8).
Autonomous electric commercial vehicle for difficult operating conditions

Nowadays development of autonomous vehicle driving control systems is a global trend. The growing autonomous vehicles market is stimulated by a variety of competitions and awards. This article introduces the background and the first steps taken by the research team of Nizhny Novgorod State Technical University named after R.E. Alekseev (NGTU). The research is supported by GAZ Group’s United Engineering Centre and by PAO GAZ experts. The control system in question is developed for operation in severe weather and road conditions of the Russian Federation. An electrical platform is used as chassis for the control system. The working components of the autonomous vehicle driving control system, its location and the area of operation are considered in the article. The software to operate every module of the system has been developed; the system operation has been tested.
A Study of Patient Clinician Interaction and Abnormal Illness Behaviours among Subjects with Chronic Non Organic Pain

Introduction: Patient clinician interaction is an important component of Abnormal Illness Behaviours (AIB) and can have significant impact on the patients’ as well health care settings. AIB has been measured more with self-report scales compared to objective rating scales. This study assessed patient clinician interaction among in chronic pain using an objective scale, Illness Behaviour Assessment Schedule (IBAS). Method: Details of demography and illness were collected using a semis-structured schedule. IBAS was administered to 301 adult subjects with chronic non-organic pain to assess patient clinical interaction and illness behaviour patterns. Findings: Majority of the sample consisted of women (N=208; 69%). The mean duration of pain symptoms in years was 5.78± 5.43. Majority of the subjects did not acknowledge or were not sure of receiving any explanation for their illness. Subjects recalled the causal explanation as having both psychological and somatic causes. Nearly 70% of the subjects attributed their affective disturbance to somatic problems. Gender differences were noted in communication of affect with more men having moderate to marked inhibition. (Chi square 7.78, p=0.005). Conclusions: This study highlights that patients often do not recall the explanations provided for their symptoms and may attribute their symptoms based on their own beliefs. This may correlate to abnormal illness behaviours. It is important to patient clinician interaction regarding the pain symptoms and attribution for appropriate management.
Mycobiota and aflatoxin B1 contamination of rainbow trout (Oncorhinchus mykiss) feed with emphasis to Aspergillus section Flavi

In the present study, natural occurrence of fungi and aflatoxin B1 (AFB1) in trout pellet feed and feed ingredients randomly obtained from feed markets was investigated. The samples were cultured on the standard isolation media for 2 weeks at 28 oC. Identification of fungal isolates was implemented based on the macro- and microscopic morphological criteria. AFB1 was detected using high performance liquid chromatography (HPLC). Based on the results obtained, a total of 109 fungal isolates were identified of which Aspergillus was the prominent genus (57.0%), followed by Penicillium (12.84%), Absidia (11.01%) and Pseudallscheria (10.10%). The most frequent Aspergillus species was A. flavus (60.66%) isolated from all the feed ingredients as well as pellet feed. Among 37 A. flavus isolates, 19 (51.35%) were able to produce AFB1 on YES broth in the range of 10.2 to 612.8 µg/g fungal dry weight. HPLC analyses of trout feed showed that pellet feed and all feed ingredients tested except gluten were contaminated with different levels of AFB1 in the range of 1.83 to 67.35 µg/kg. Unacceptable levels of AFB1 were reported for feed including soybean, fish meal and wheat. These results indicate the importance of AF contamination of trout feed in amounts higher than the acceptable level as a risk factor for fish farming production.
ACOUSTIC SCENE CLASSIFICATION WITH FULLY CONVOLUTIONAL NEURAL NETWORKS AND I-VECTORS Technical Report

This technical report describes the CP-JKU team’s submissions for Task 1 Subtask A (Acoustic Scene Classification, ASC) of the DCASE-2018 challenge. Our approach is still related to the methodology that achieved ranks 1 and 2 in the 2016 ASC challenge: a fusion of i-vector modelling using MFCC features derived from left and right audio channels, and deep convolutional neural networks (CNNs) trained on spectrograms. However, for our 2018 submission we have put a stronger focus on tuning and pushing the performance of our CNNs. The result of our experiments is a classification system that achieves classification accuracies of around 80% on the public Kaggle-Leaderboard.
SOSYAL MEDYA DAVRANIŞININ OLUŞUMU: ÇEVRİMİÇİ ORTAMLARDA GÜVEN, SOSYAL SERMAYE VE SAYGINLIK İLİŞKİSİ

Bu calismanin amaci universite gencliginin sosyal medyada paylasimlarini hangi davranis teorisi baglaminda gerceklestirdigini ve paylasim yapma niyetine yonelik tutumu etkileyen faktorleri degerlendirmektir. Bu dogrultuda calisma, genclerin sosyal medya mecralarinda paylasima iliskin tutumlarini aciklayan e-sosyal sermaye, e-sosyal guven ve sosyal medyaya guven gibi cevresel faktorler ile sayginlik gibi kisisel faktorler temelinde tasarlanmistir. Alan arastirmasina konu olan veriler 1232 universite ogrencisiyle yapilan anket calismasi neticesinde elde edilmistir. Calismanin teorik cercevesi temelinde olusturulan arastirma modeli iki asamali olarak yapisal esitlik modellemesiyle (YEM) analiz edilmistir. Calisma sonuclari ilgili orneklem cercevesinde degerlendirildiginde universite genclerinin sosyal medyada paylasimlarini gerekcelendirilmis eylem teorisi baglaminda gerceklestirdigini gostermektedir. Ayrica, sosyal medyaya guven, e-sosyal guven, e- sosyal sermaye ve sayginlik degiskenlerinin sosyal medyada paylasim yapma niyetine yonelik tutum uzerinde olumlu bir etkiye sahip oldugu tespit edilmistir.
Computational Vision for Automatic Tracking and Objective Estimation of Mobile Robot Trajectory

Automatic tracking and evaluation of moving-object trajectories is critical in many applications such as performance estimation of mobile robot navigation. Mobile robot is an effective platform for stimulating student motivation at K-12 institutions as well as a good tool for rigorous engineering practices in colleges, universities, and graduate schools. Developing new mobile robot platforms and algorithms requires objective estimation of navigation performance in a quantitative manner. Conventional methods to estimate mobile robot navigation typically rely on manual usage of chronometer to measure the time spent for the completion of a given task or counting the success rate on the task. This paper proposes an alternative; a multi-camera vision system that can automatically track the movement of mobile robot and estimate it in terms of physics-based profiles: position, velocity, and acceleration of the robot in the trajectory with respect to a user-defined world-coordinate system. The proposed vision system runs two synchronized cameras to simultaneously capture and track the movement of the robot at 30 frames per second. The system runs a homography-based projection algorithm that converts the view-dependent appearance of the robot in the camera images to a view-independent orthographic projection mapped on the registered world coordinate system. This enables the human evaluator to view and estimate the robot navigation from a virtual top-down view embedded with the physics-based profiles regardless of the actual cameras’ viewing positions. The proposed system can also be used for other domains including highway traffic monitoring and intelligent video surveillance.
The 2018 DAVIS Challenge on Video Object Segmentation-CVPR 2018 Workshops

In this work, we propose Context-based Instance Segmentation for video object segmentation in two passes. Namely, in the first pass, we estimate the main properties of each instance (i.e., human/non-human, rigid/deformable, known/unknown category) by propagating its initial mask to other frames. We employ Instance Re-Identification Flow in this pass. The result of the first pass helps our system to automatically select the appropriate scheme for instance segmentation in the second pass. In the second pass, we process human and non-human instances separately. For human instance, we employ Mask R-CNN to extract human segments, OpenPose to merge fragments (in a frame), and object flow to correct and refine the result across frames. For non-human instance, if the instance has a wide variation in its appearance and it belongs to known categories (which can be inferred from the initial mask), we use Mask-RCNN for instance segmentation. If the instance is nearly rigid, we synthesize images from the first frame of a video sequence. We use affine and non-rigid deformations, together with illumination changes, to generate variants of the initial mask. To choose appropriate background for synthesized images, we retrieve images from the Places365 dataset having the similar scene category and scene attributes with the original frame. FCNs, including DeepLab2 and OSVOS, are trained on our synthesized dataset for each instance. For a deformable object in an unknown category, we reuse the baseline result from the first pass. Finally, instances in each frame are merged based on their depth values, using DCNF-FCSP, together with human and non-human object interaction and rare object priority. ⇤Corresponding author. Email: tmtriet@fit.hcmus. edu.vn
Three dimensional dose verification of VMAT plans using the Octavius 4D dosimetric system

The Octavius 4D dosimetric system generates a 3D dose matrix based on a measured planar dose and user supplied Percentage Depth Dose (PDD) data. The accuracy of 3D dose matrices reconstructed by the Octavius 4D dosimetric system was systematically studied for an open static field, an open arc field and clinical VMAT plans. The Octavius reconstructed 3D dose matrices were compared with the Treatment Planning System (TPS) calculated 3D dose matrices using 3D gamma (γ) analysis with 2%/2mm and 3%/3mm tolerance criteria. The larger detector size in the 2D detector array of the Octavius system resulted in failed voxels in the high dose gradient regions. For the open arc fields mean (1σ) γ pass rates of 84.5(8.9) % and 94.2(4.5) % were observed with 2%/2mm and 3%/3mm tolerance criteria respectively and for clinical VMAT plans mean (1σ) γ pass rates of 86.8(3.5) % and 96.7(1.4) % were observed.