Miracle-dz/UniFAR-FTUs huggingface dataset:
ATTILA 4.0: Lagrangian advective and convective transport of passive tracers within the ECHAM5/MESSy (2.53.0) chemistry–climate model

Abstract. We have extended ATTILA (Atmospheric Tracer Transport in a LAgrangian model), a Lagrangian tracer transport scheme, which is online coupled to the global ECHAM/MESSy Atmospheric Chemistry (EMAC) model, with a combination of newly developed and modified physical routines and new diagnostic and infrastructure submodels. The new physical routines comprise a parameterisation for Lagrangian convection, a formulation of diabatic vertical velocity, and the new grid-point submodel LGTMIX to calculate the mixing of compounds in Lagrangian representation. The new infrastructure routines simplify the transformation between grid-point (GP) and Lagrangian (LG) space in a parallel computing environment. The new submodel LGVFLUX is a useful diagnostic tool to calculate online vertical mass fluxes through horizontal surfaces. The submodel DRADON was extended to account for emissions and changes of 222Rn on Lagrangian parcels. To evaluate the new physical routines, two simulations in free-running mode with prescribed sea surface temperatures were performed with EMAC–ATTILA in T42L47MA resolution from 1950 to 2010. The results show an improvement of the tracer transport into and within the stratosphere when the diabatic vertical velocity is used for vertical advection in ATTILA instead of the standard kinematic vertical velocity. In particular, the age-of-air distribution is more in accordance with observations. The global tropospheric distribution of 222Rn, however, is simulated in agreement with available observations and with the results from EMAC in grid space for both Lagrangian systems. Additional sensitivity studies reveal an effect of inter-parcel mixing on the age of air in the tropopause region and the stratosphere, but there is no significant effect for the troposphere.
CUNI System for the WMT18 Multimodal Translation Task

We present our submission to the WMT18 Multimodal Translation Task. The main feature of our submission is applying a self-attentive network instead of a recurrent neural network. We evaluate two methods of incorporating the visual features in the model: first, we include the image representation as another input to the network; second, we train the model to predict the visual features and use it as an auxiliary objective. For our submission, we acquired both textual and multimodal additional data. Both of the proposed methods yield significant improvements over recurrent networks and self-attentive textual baselines.
The rHEALPix Discrete Global Grid System

In light of the new standard for Discrete Global Grid Systems (DGGS) currently being proposed by the Open Geospatial Consortium (OGC), we revisit our earlier work on defining the rHEALPix DGGS. This paper briefly restates the definition of the rHEALPix DGGS and shows how the cell geometries, and schema for cell identifiers are both compliant with the standard. We then show that the fundamental topological operators, required by the standard can be implemented directly by manipulation of the cell identifiers without reference to or knowledge of traditional coordinates.
Error Treatment in EFL S-CMC Tasks: An Analysis of Corrective Feedback

This research is a classroom-based, exploratory and descriptive study to better understand how error treatment during communicative synchronous computer mediated communication (S-CMC) tasks in EFL classroom happens. 42 learners participated in S-CMC tasks, and their chatscripts were analyzed according to the error treatment sequence. Particularly, the analysis focused on the frequency distribution of the different error types, the availability of corrective feedback, uptake and repair, and the effects of corrective feedback. The findings support the idea, which has been demonstrated by preceding studies, that when language learning is solely experiential and focused on communicative success, some linguistic features may not develop to targetlike accuracy. In addition, this study shows that S-CMC may offer us great chances for error treatment in that learners’ synchronous interactions are recorded. It emphasizes the role of language teachers, especially in a communicative EFL setting, and it suggests the need for the study to examine the post-treatment of errors in S-CMC tasks.
Resistance assessment of grapevine rootstocks used in Chile to the root-knot nematodes Meloidogyne ethiopica, M. hapla, and M. javanica

The rootstocks 1103 P, 101-14, K 5BB, SO4, and 3309 were assessed to determine their resistance to the three common Meloidogyne species present in Chilean vineyards, M. ethiopica , the most frequent species, M. hapla and M. javanica . Their response was compared to three ungrafted cultivars, Thompson Seedless, Pinot Noir and Chardonnay. To perform this study, two month-old plants produced from cuttings were inoculated with 5,000 eggs per 3-L pots, filled with steamed substrate and kept in a glasshouse covered with a black mesh to intercept 30% of sun light and avoid heating of the substrates. After a growth period of six months, plants were removed from the pots, and resistance was determined by measuring root weights, the number of galls and eggs per g of root, and second stage juveniles per 250 cm 3 of soil. Results showed that the five rootstocks were resistant to the parasitism of the three Meloidogyne species, since their reproduction was limited and differed from two of the cultivars. Chardonnay was the most susceptible cultivar, mainly to the high level of parasitism by M. ethiopica , while Pinot Noir was moderately susceptible and Thompson Seedless showed the lowest susceptibility. Los portainjertos 1103 P, 101-14, K 5BB, SO4, 3309, de uso frecuente para la plantacion de vides en Chile, fueron evaluados para determinar su resistencia a tres especies de nematodos del genero Meloidogyne, M. ethiopica , la especie de mayor frecuencia en vinedos en Chile, M. hapla y M. javanica . Junto con ello se evaluo la susceptibilidad de tres cultivares no injertados, Thompson Seedless, Pinot Noir y Chardonnay. Para ello, al inicio de la primavera, plantas nuevas de 2 meses de desarrollo producidas a partir de estacas, cultivadas en macetas de 3 L con sustratos esteril, fueron inoculadas con 5.000 huevos por maceta y mantenidas en un sector habilitado con malla raschel durante 6 meses. Para determinar su resistencia, al termino del periodo de cultivo las plantas se sacaron de las macetas y se determino su peso radical, numero de agallas por masa de raiz, cantidad de huevos por gramo de raiz y numero de juveniles de segundo estado en el suelo. Los resultados mostraron que los cinco portainjertos se comportaron como resistentes al ataque de las tres especies de Meloidogyne . De las variedades cultivadas, Chardonnay mostro una alta susceptibilidad, especialmente frente a M. ethiopica , Pinot Noir se comporto moderadamente susceptible, en tanto que, Thompson Seedless mostro una resistencia moderada.
Enhancement of radiation effect by Guduchi (Tinospora cordifolia) in HeLa cells

The radiosensitizing effect of various guduchi (Tinospora cordifolia Miers, Menispermaceae) extracts, i.e., pretreatment with 10 µg/ml of methanol (Met), aqueous (Aqu) or methylene chloride (Mch) extracts, was studied in the HeLa cells exposed to 0, 0.5, 1, 2, or 3Gy of ? -radiation. The irradiation of cells resulted in a dose-dependent decline in the clonogenicity of cells expressed as reduction in cell survival. Treatment of HeLa cells with Met, Aqu or Mch extract before exposure to different doses of ? -radiation resulted in a significant decline in the cell survival when compared with the phosphate-buffered saline (PBS) + irradiation group. The highest loss in the clonogenicity was observed in Mch + irradiation group, where the cell survival was lower than doxorubicin (Dox) + irradiation group. Conversely, the frequency of micronuclei increased in a dose-dependent manner in all the groups and a significant elevation in micronuclei frequency was observed in Met + irradiation, Aqu + irradiation, Mch + i.
Characterization of the natural chemical and osmotic environment of early wheat embryogenesis

Soluble carbohydrates, amino acids, and major inorganic ions were quantified and compared with the total osmolarity of the ovule. Most of the analyzed components increased rapidly in concentration, reaching a peak at 1 day post anthesis (DPA) and decreasing quickly 1 day later. Within this time period, the osmolarity decreased from 1.49 to 1.18 MPa. The osmolarity then increased to 1.39 MPa at 4 DPA, and yet the overall concentration of analyzed molecules decreased. At 1 DPA, inorganic ions were observed at levels that could produce a high osmolarity (1.11 MPa), followed by the carbohydrates (0.37 MPa) and amino acids (0.07 MPa). Maltose was detected in ovules only from 0 to 2 DPA. Inositol was abundant in the ovules on the day of anthesis, but decreased to non-detectable levels after 4 DPA. This suggested that ovules allow the rapid entry of solutes into the syncytial endosperm after fertilization, but are osmotically buffered through the increase and decrease of partly identified substances. Specific gravity tests on the liquid squeezed from young endosperm sukpported this new hypothesis. Osmolarity in ovules seems only indirectly related to morphogenetic regulation mechanisms, and it may play a lesser role than the fluctuations of certain specific substances. The observed chemical changes offer insights into the rapidly varying nutritional needs of proembryos. Thus, in this research yielded a useful complex amino acid formula, derived from knowledge of the natural environment of the proembryo, and also an improved proembryo and ovule culture medium.
Effects on Students Perceptual Evaluations of the Wall Colors Used in Design Studios by the Virtual Reality Method

In this study, it was aimed to determine the perceived quality of three modeled virtual design studios which have the same characteristics but different colors (warm, cool and neutral) and to determine whether there was a difference between the real space and the evaluations made in the virtual space. Accordingly, it was assumed that the wall coloring of the virtual studio space models that were modeled could affect the perceptions of the students and that virtual space evaluations would be in parallel with real space evaluations. To test the assumption, the study modeled the environments of three design studios with different colors assumed to exist at a design studio of the Selcuk University and students were asked to evaluate these virtual spaces with the aid of virtual reality goggles. As a result, it has been determined that there was no difference between the perceptual evaluations of real and virtual spaces designed with the same features. In addition, according to the spatial scale, it was determined that the cool colored space were perceived as “more roomy” and “more inviting” by the students compared to the warm colored space and that the cool colored space was also evaluated more positively for the social adaptation and individual productivity scales.
Statistical multiplexing of video sources for packet switching networks

Title of Thesis: Statistical Multiplexing of Video Sources For Packet Switching Networks Krishna Kancherla, Master of Science in Electrical Engineering, 1989 Thesis Directed by: Dr. Constantine Manikopoulos, Associate Professor Communication networks are fast evolving towards truly integrated networks handling all types of traffic. They employ integrated switching technologies for voice, video and data. Statistical or asynchronous time division multiplexing of full motion video sources is an initial step towards packetized video networks. The main goal is to utilize the common communication channel efficiently, without loosing quality at the receiver. This work discusses the concept of using statistical multiplexing for packet video communications. The topology of a single internal packet network to support ISDN services has been adoptedf Simulations have been carried out to demonstrate the statistical smoothing effect of packetized video in the networks having high speed links. Results indicate that the channel rate per source decreased in an exponential manner as the number of sources increased. An expression for the average usage time t of the channel has been derived in terms of channel rate per source and the number of sources multiplexed. Also the average usage time of the channel is higher for buffered data than that of the multiplexed data. The high speed communication links in the internal network are lightly loaded, which indicates that these links can accommodate more data. STATISTICAL MULTIPLEXING OF VIDEO SOURCES FOR PACKET SWITCHING NETWORKS by Krishna Kancherla Thesis submitted to the Faculty of Graduate School of . the New Jersey Institute of Technology in partial fulfillment of the requirements for the degree of Master of Science in Electrical Engineering 1989
Intake, apparent digestibility and ingestion behavior in Holstein steers fed diets containing Tifton 85 hay with different particle sizes

The intake, the apparent digestibility of nutrients and the ingestion behavior of four Holstein steers with average weight of 300 kg and 20 months of age, receiving diets containing Tifton 85 hay with different particle sizes (5, 7, 10 mm and whole) were evaluated. A 4 × 4 Latin square experimental design with four steers and four periods was used. Intakes of dry matter, organic matter, crude protein, ether extract, neutral detergent fiber, acid detergent fiber, total carbohydrates and non-structural carbohydrates were not influenced by the different granulometric profiles of the experimental diets. The DM digestibility were different between diets with particles size of 7 and 10 mm (67.31 and 54.95%, respectively). However, these diets were similar to that with 5 mm of particle size and whole hay, which showed intermediate values, with mean of 63.62%. The total feeding time of the animals that received diets with particles size of 7, 10 mm and whole did not differ. The Tifton 85 hay with different particles size did not affect the intake, digestibility of nutrients and the ingestion behavior of Holstein steers fed total mixed ration.
Specific smartphone uses and how they relate to anxiety and depression in university students: a cross-cultural perspective

ABSTRACT People around the world spend hours of their daily lives using smartphones; therefore, it is important to conduct cross-cultural research on the effects of smartphone use on health and well-being as culture influences values, motivations and communication patterns. The purpose of this study was to explore 5 popular uses of the smartphone – messaging, browsing the Internet, posting social content, reading social content, and playing games – how they relate to anxiety and depression scores, and how they vary depending on the country of the participants: Spain, the United States, and Colombia. In all three countries the ranking of most popular uses was the same: (1) Messaging, (2) Reading social content, and (3) Browsing the Internet. In the USA, game playing contributed to anxiety scores whereas reading social content was a protective factor; regarding depression scores, text messaging was a contributing factor. In Spain, browsing the Internet contributed to anxiety scores; regarding depression scores, messaging was a contributing factor and posting social content was a protective factor. In Colombia, no specific use influenced anxiety scores; regarding depression scores, only game playing was a protective factor. Our results showed that in all the countries, problematic smartphone use contributed to anxiety scores.
Prediction of neurodegenerative diseases from functional brain imaging data

Neurodegenerative diseases are a challenge, especially in the developed society where life expectancy is high. Since these diseases progress slowly, they are not easy to diagnose at an early stage. Moreover, they portray similar disease features, which makes them hard to differentiate. In this thesis, the objective was to devise techniques to extract biomarkers from brain data for the prediction and classification of neurodegenerative diseases, in particular parkinsonian syndromes. We used principal component analysis in combination with the scaled subprofile model to extract features from the brain data to classify these disorders. Thereafter, the features were provided to several classifiers, i.e., decision trees, generalized matrix learning vector quantization, and support vector machine to classify the parkinsonian syndromes. A validation of the classifiers was performed. The decision tree method was compared to the stepwise regression method which aims at linearly combining a few good principal components. The stepwise regression method performed better than the decision tree method in the classification of the parkinsonian syndromes. Combining the two methods is feasible. The decision trees helped us to visualize the classification results, hence providing an insight into the distribution of features. Both generalized matrix learning vector quantization and support vector machine are better than the decision tree method in the classification of early-stage parkinsonian syndromes. All the classification methods used in this thesis performed well with later disease stage data. We conclude that generalized matrix learning vector quantization and decision tree methods can be recommended for further research on neurodegenerative disease classification and prediction.
Asymptotic Outage Analysis on Dual-Branch Diversity Receptions Over Non-Identically Distributed Correlated Lognormal Channels

It is challenging to quantify the left tail behavior of the cumulative distribution function of a sum of lognormal random variables, especially when they are correlated and non-identically distributed. The mathematical intractability hampers the analysis on diversity receptions over lognormal fading channels. In this paper, a novel asymptotic technique is exploited to study non-identically distributed dual-branch lognormal fading channels with correlation. Closed-form asymptotic outage probability expressions are derived for maximum-ratio combining (MRC), equal-gain combining (EGC), and selection combining (SC). Three counterintuitive facts are revealed: 1) one of the two channels contributes no asymptotic performance gain to the diversity reception systems under certain conditions, implying that a link can be discarded without causing asymptotic performance loss; 2) SC outperforms EGC under certain conditions; and 3) the outage probability of SC is arbitrarily close to that of MRC under certain conditions. The new result reveals insights into the long-standing problem of asymptotic analysis for correlated lognormal fading channels, paving the way for analysis on more general channel models. This paper also provides an efficient approach to evaluate the non-identically distributed lognormal fading channels at a high signal-to-noise ratio. Practically, the analytical results prevent some redundant units that contribute no performance gain.
Ringing Suppression in a Controller Area Network With Flexible Data Rate Using Impedance Switching and a Limiter

The ringing and the resulting asymmetry in the propagation delay are the main causes of bandwidth degradation and communication errors in a controller area network (CAN) with flexible data rate. Therefore, in this paper, the mechanism of ringing is analyzed, and the ringing suppression circuit is proposed based on the analysis. The proposed circuit includes an impedance matching resistor and a forward-biased diode for terminating the repetition of reflections and limiting the magnitude of the ringing. These components are temporarily connected by operating a switch that is controlled by the TxD signal of a CAN controller so that the ringing suppression circuit only engages when necessary and at the correct time. The performance of the ringing suppression circuit is verified by experiments. The experimental results show that the proposed circuit keeps the ringing adequately suppressed and the good symmetry in the propagation delay across the physical bus is possessed.
Comparing CNN and Human Crafted Features for Human Activity Recognition

Deep learning techniques such as Convolutional Neural Networks (CNNs) have shown good results in activity recognition. One of the advantages of using these methods resides in their ability to generate features automatically. This ability greatly simplifies the task of feature extraction that usually requires domain specific knowledge, especially when using big data where data driven approaches can lead to anti-patterns. Despite the advantage of this approach, very little work has been undertaken on analyzing the quality of extracted features, and more specifically on how model architecture and parameters affect the ability of those features to separate activity classes in the final feature space. This work focuses on identifying the optimal parameters for recognition of simple activities applying this approach on both signals from inertial and audio sensors. The paper provides the following contributions: (i) a comparison of automatically extracted CNN features with gold standard Human Crafted Features (HCF) is given, (ii) a comprehensive analysis on how architecture and model parameters affect separation of target classes in the feature space. Results are evaluated using publicly available datasets. In particular, we achieved a 93.38% F-Score on the UCI-HAR dataset, using 1D CNNs with 3 convolutional layers and 32 kernel size, and a 90.5% F-Score on the DCASE 2017 development dataset, simplified for three classes (indoor, outdoor and vehicle), using 2D CNNs with 2 convolutional layers and a 2x2 kernel size.
SphereDiar - an efficient speaker diarization system for meeting data

The objective of speaker diarization is to determine who spoke and when in a given audio stream. This information is useful in multiple different speech related tasks such as speech recognition, automatic creation of rich transcriptions and text-to-speech synthesis. Moreover, speaker diarization can also play a central role in the creation and organization of speech-related datasets. Speaker diarization is made difficult by the immense variability in speakers and recording conditions, and the unpredictable and overlapping speaker turns of spontaneous discussion. Especially diarization of meeting data has been very challenging. Even the most advanced speaker diarization systems still struggle with this type of data. In this thesis, a novel speaker diarization system, named SphereDiar and designed for the diarization of meeting data, is proposed. This system combines three novel subsystems: the SphereSpeaker neural network for speaker modeling, a segmentation method named Homogeneity Based Segmentation and a clustering algorithm Top Two Silhouettes. The system harnesses up-to-date deep learning approaches for speaker diarization and addresses the problem of overlapping speech in this task. Experiments are performed on a dataset consisting of over 200 meetings. The experiments have two main outcomes. Firstly, the use of Homogeneity Based Segmentation is not vital for the system. Thus, the configuration of SphereDiar can be simplified by omitting segmentation. Furthermore, SphereDiar is shown to surpass the performance of two different state-of-the-art speaker diarization systems.