Miracle-dz/UniFAR-FTUs huggingface dataset:
YOUNG EUCALYPTUS PLANTS

Trinexapac-ethyl and sulfometuron-methyl are the most widely used ripeners in sugarcane. The application is performed by airborne spraying. Thus, if weather conditions are unfavorable, spray drift to neighboring areas may occur. The objective of this study was to assess the selectivity of the plant growth regulators trinexapac-ethyl and sulfometuronmethyl, used as sugarcane ripeners, to eucalyptus (Eucalyptus urograndis) young plants. The experiment was installed in an eucalyptus commercial yield area, in the municipality of Tambaú, state of São Paulo, Brazil, and arranged in a 2 x 8 factorial design in randomized blocks with four replications. The treatments studied were trinexapac-ethyl and sulfometuronmethyl, sprayed in eight doses, 0; 1.0; 2.5; 5.0; 10; 25; 50 and 100% of the dose used in sugarcane as ripeners (200 g ha-1 of trinexapac-ethyl and 15 g ha-1 of sulfometuron-methyl). Chemical ripeners were applied on eucalyptus plants with 48 cm in height on average; 10.1 branches; 4.5 mm of stem diameter and 44.3 cm of crown diameter, at 46 days after seeding. Trinexapac-ethyl was selective to eucalyptus and stimulated crown diameter growth. At higher doses, sulfometuron-methyl promoted severe noticeable injuries in eucalyptus plants, such as apical bud death. However, during the assessment period the plants recovered and the visual symptoms of phytotoxicity and growth alterations were not observed at 60 days after application. The plant growth regulators trinexapac-ethyl and sulfometuron-methyl were selective to eucalyptus young plants.
Short-term Underground Mine Scheduling

The operational performance of an underground mine depends critically on how the production is scheduled. Increasingly advanced methods are used to create optimized long-term plans, and simultaneously the actual excavation is getting more and more automated. Therefore, the mapping of long-term goals into tasks by manual short-term scheduling is becoming a limiting segment in the optimization chain. In this thesis we study automating the short-term mine scheduling process, and thus contribute to an important missing piece in the pursuit of autonomous mining. First, we clarify the fleet scheduling problem and the surrounding context. Based on this knowledge, we propose a flow shop that models the mine scheduling problem. A flow shop is a general abstract process formulation that captures the key properties of a scheduling problem without going into specific details. We argue that several popular mining methods can be modeled as a rich variant of a k-stage hybrid flow shop, where the flow shop includes a mix of interruptible and uninterruptible tasks, after-lags, machine unavailabilities, and sharing of machines between stages. Then, we propose a Constraint Programming approach to schedule the underground production fleet. We formalize the problem and present a model that can be used to solve it. The model is implemented and evaluated on instances representative of medium-sized underground mines. After that, we introduce travel times of the mobile machines to the scheduling problem. This acknowledges that underground road networks can span several hundreds of kilometers. With this addition, the initially proposed Constraint Programming model struggles with scaling to larger instances. Therefore, we introduce a second model. The second model does not solve the interruptible scheduling problem directly; instead, it solves a related uninterruptible problem and transforms the solution back to the original time domain. This model is significantly faster, and can solve instances representative of large-sized mines even when including travel times. Lastly, we focus on finding high-quality schedules by introducing Large Neighborhood Search. To do this, we present a domain-specific neighborhood definition based on relaxing variables corresponding to certain work areas. Variants of this neighborhood are evaluated in Large Neighborhood Search and compared to using only restarts. All methods and models in this thesis are evaluated on instances generated from an operational underground mine.
VESUS: A Crowd-Annotated Database to Study Emotion Production and Perception in Spoken English

We introduce the Varied Emotion in Syntactically Uniform Speech (VESUS) repository as a new resource for the speech community. VESUS is a lexically controlled database, in which a semantically neutral script is portrayed with different emotional inﬂections. In total, VESUS contains over 250 distinct phrases, each read by ten actors in ﬁve emotional states. We use crowd sourcing to obtain ten human ratings for the perceived emotional content of each utterance. Our unique database construction enables a multitude of scientiﬁc and technical ex-plorations. To jumpstart this effort, we provide benchmark performance on three distinct emotion recognition tasks us-ing VESUS: longitudinal speaker analysis, extrapolating across syntactical complexity, and generalization to a new speaker.
Li-decorated Pmmn 8 phase of borophene for hydrogen storage . A van der Waals corrected density-functional theory study

We performed standard and van der Waals-corrected density functional theory calculations to investigate the hydrogen storage capacity of a phase of borophene with Pmmn symmetry and nonzero thickness. This borophene sheet (Pmmn8) has 8 atoms in its unit cell and is more stable than the planar α sheet and that the corrugated Pmmn2 sheet (2 atoms in the unit cell). Our results show that, in pristine form, the Pmmn8 sheet is not suited for hydrogen storage applications. However, decoration with Li atoms and strain increase the hydrogen storage ability of the sheet. We performed also a detailed quantum chemical topological analysis that shows that the B-Li interaction in the hydrogenated Li-decorated Pmmn8 sheet is ionic. Our results for the adsorption of H2 on the Li-decorated Pmmn8 sheet are compared with those obtained for the adsorption of H2 on Ti-decorated zigzag graphene nanoribbons.
Pi-Crust : A Raspberry Pi Cluster Implementation

Raspberry Pi is revolutionizing the computing industry. Originally designed to provide low cost computers to schools it quickly expanded far beyond that. With this inexpensive technology you can accomplish tasks previously unexplored. One such set up is a cluster computer to run parallel jobs. Many systems built for parallel computing jobs are either very expensive or unavailable to those outside of academia. Supercomputers are extremely expensive to own, use, power and maintain. Even though average desktop computers have come down in price the expense can still get quite high if you need a larger amount of processing power. In this project, we take ten Raspberry Pi 2 computers and connect them over an ethernet network to build a parallel version of a supercomputer. We show how one can be built inexpensively and compare the performance of our system to both desktop machines and supercomputers in use by academia. We look at a price comparison as well as performance and show the differences between the older versions of the Raspberry Pi cluster computers and our own implementation. Our results show that our Pi cluster implementation significantly outperforms previous Pi cluster projects with the cost being similar. This project strongly made us believe that the Raspberry Pi is a great learning platform for academia and personal use and the processing power at the cost involved is hard to beat.
Character-Aware Sub-Word Level Language Modeling for Uyghur and Turkish ASR

Uyghur and Turkish are two typical agglutinative languages, which suffer heavily from the data sparsity problem. Due to this, we first apply a statistical morphological segmentation and change the number of morphs to get a better sub-word level automatic speech recognition (ASR) system. The best systems, which yield 2.03% and 1.65% absolute WER reductions from the word level systems for Uyghur and Turkish respectively, are used for further n-best rescoring. To further alleviate the data sparsity problem, we use both convolutional neural network (CNN) based and bi-directional long short-term memory (BLSTM) based character-aware language models on the two languages. In order to alleviate the information missing of the middle steps of the BLSTM based character aware language model, we propose to use the weighted average of each time-steps’ outputs. The proposed weighting methods can be divided into three categories: decay based, position-based and attention-based. Results show that the decay based weighting method leads to the most significant WER reductions, which are 2.38% and 1.96%, compared with the sub-word level 1-pass ASR system for Uyghur and Turkish respectively.
PHYTOSOCIOLOGICAL ANALYSIS OF WOODY SPECIES UNDER BURNT AND UNBURNT COMMUNITIES AT PAURI GARHWAL , WESTERN HIMALAYA , INDIA

Fire is perceived as one of the dramatic natural forces determining the biotic community over time (Ahlgren 1974). Vegetation and fire are interrelated so that a change in any of two variables can affect the other (Ruiliang et al., 2007). Forest fires represent a considerable threat and are primarily disturbance to the forests of Uttarakhand, India. The correlation among fire and Pinus ecosystem in the vegetation of Central Himalaya is one of the most distinguished examples of ecosystem dependency on disturbance mostly in Oak ecosystems. Earlier Singh et al.,1984 examined that the Pine is light demanding, fire-adapted but fire-promoting species and Oak forests being inflammable had experience a good deal from pine spreading fires (Champion et al., 1968). Literature review suggests that open canopy forests are more inclined to fire than closed forests as the floor in open forests is drier than closed forests due to a greater extent of sunlight infiltration (Stolle et al., 2003). The relationship flanked by fire severity and plant community response is relevant not only in wildfire settings but also for assessing management performances as in prescribed burning (Miller et al., 2000). Among the western Himalayan region, Uttarakhand is reported to have the highest incidences of forest fires. The devastating forest fire of 1995 mainly set in Pinus slopes results in a catastrophe effects to the large tracts of forests of Uttarakhand. In 2016 ferocious forest fire cover become prominent and wreaking havoc in almost all the forest regions of Uttarakhand. While by applying intentional prescribed fire (Controlled burning) typically acts well if handled suitably. The objectives of the present examination were to find out the impacts of a prescribed fire on aboveground woody vegetation (structure and composition) on Burnt protected site (BPS) and on control site as Unburnt Protected Site (UPS).
Effects of high rice diet on growth performance, nutrients apparent digestibility, nitrogen metabolism, blood parameters and rumen fermentation in growing goats.

This study was conducted to evaluate the effects of high rice grain diet on apparent nutrient digestibility, growth performance, nitrogen digestion, blood parameters and rumen fermentation in goats. Sixteen growing goats were divided into 2 groups and fed a normalconcentrate diet (NC, 55% concentrate of dry matter; n=8) or a high concentrate diet (HC, 90% concentrate of dry matter; n=8) for 5 wk. Growth performance, nutrients digestibility, nitrogen digestion, blood parameters and ruminal fermentation were measured. Total weight gain and average daily gain increased in the HC group (P<0.01). Digestibility of Neutral Detergent Fibre (NDF) and Acid Detergent Fibre (ADF), nitrogen intake and digested nitrogen also increased (P<0.05) by HC feeding. Triglycerides, cholesterol, high density lipoprotein and low-density lipoprotein concentrations in the blood decreased (P<0.05). HC diet feeding decreased (P<0.01) the pH value, acetate level and ratio of acetate to propionate, but increased (P<0.05) the concentrations of propionate, valerate and total volatile fatty acids in the rumen. These findings revealed that the HC diet could promote the growth of growing goats, change the ruminal fermentation pattern and lipid metabolism in the blood, but cause subacute ruminal acidosis, which might increase the risk of body health.
Selecting an Optimal Portfolio for Investment in Stocks in India : A Sectoral Approach

Investment in stocks may be made individually or through portfolio managers. This study attempts at selecting an optimal portfolio for investment in Indian equity stocks belonging to specific economic sectors. After reviewing the relevant literature, the objectives and research methodology of the study have been spelt out. This is followed by a coverage of the concepts and definitions which are relevant for this study. A comparison of the different approaches to select an optimum portfolio has been made to get an overview of the relative measures.
Algorithm 1 : Algorithm to combine doctrees Data : List of doctrees doctrees Result : surveytree

Surveys are helpful in quick knowledge acquisition in a given topic. However, in rapidly advancing and specialized fields like Natural Language Processing (NLP) and Artificial Intelligence (AI), surveys quickly become outdated or simply do not exist. Currently, automatically generated surveys in these two domains are not yet reliable enough for general use. One aspect of automatically generated surveys that has room to improve on is its structure. Current systems that attempt this typically disregard the hierarchical structure within documents and instead focus on a one dimensional ordering of extracted text. In this paper, we propose a method where the hierarchical structures of input documents are parsed into trees which are then combined to generate a hierarchical structure for a survey. Initial tests of the system yield promising results that show both potential of using hierarchical structure in survey generation and that certain aspects of the system still have room to improve.
The Effect of Disease Activity Index and Level of Pain on the Disease Coping Attitudes in Rheumatoid Arthritis Patients

78 The Effect of Disease Activity Index and Level of Pain on the Disease Coping Attitudes in Rheumatoid Arthritis Patients Selçuk Mıstık, Demet Ünalan, Hatice Kayış Topaloğlu, Kemal Erol, Mustafa Çalış Erciyes University Medical Faculty Department of Family Medicine, Erciyes University Halil Bayraktar Health Services Vocational College, Erciyes University Medical Faculty Department of Physical Medicine and Rehabilitation, Kayseri ORIGINAL RESEARCH / ORİJİNAL ARAŞTIRMA 2018
On the Global Stability of Two-dimensional , Incompressible , Elastic Bars in Uniaxial Extension

When a rectangular bar is subjected to uniaxial tension, the bar usually deforms (approximately) homogeneously and isoaxially until a critical load is reached. A bifurcation, such as the formation of shear bands or a neck, may then be observed. In this paper such an experiment is modelled as the in-plane extension of a two-dimensional, homogeneous, isotropic, incompressible, hyperelastic material in which the length of the bar is prescribed, the ends of the bar are assumed to be free of shear, and the sides are left completely free. It is shown that standard, additional constitutive hypotheses on the stored-energy function imply that no such bifurcation is possible in this model due to the fact that the homogeneous isoaxial deformation is the unique absolute minimiser of the elastic energy. Thus, in order for a bifurcation to occur either the material must cease to be elastic or the storedenergy function must violate the additional hypotheses. The fact that no local bifurcations can occur under the assumptions used herein was known previously, since these assumptions prohibit the load on the bar from reaching a maximum value. However, the fact that the homogeneous deformation is the absolute minimiser of the energy appears to be a new result.
Speech-Based Web Navigation for Limited Mobility Users

We present a novel approach that introduces the strengths of voice assistants into a web browser that makes the task of web navigation a lot more accessible to all users, especially under limited mobility circumstances. Voice assistants have now been widely adopted and is providing great user experience for getting simple actions done quickly or getting a quick answer to a question. On the other hand, the benefits of voice assistants have not yet penetrated to the scenarios such as web navigation, which has so far been driven by mouse, keyboard and touchbased input only. In this paper, we demonstrate our speechbased web navigation system, and show that our system improves the completion of the web navigation task on both PC and mobile phone significantly as compared with an out-of-thebox voice assistants on this task.
Financial Crises and Unemployment : Beyond the Okun ’ s Law by

We study the additional effect of financial crises (with respect to that passing through GDP changes) on the unemployment rate. The approach is based on a theoretical framework which, starting from the “Okun’s Law”, accounts for the effect of four types of financial crises. We formulate an operational model which belongs to the family of linear MixedEffects Models and implement an Expectation-Maximization algorithm. The model is fitted to data coming from a large panel of countries for the period 1980-2005. The results show evidence of additional effects of certain types of financial crises on the unemployment rate. JEL Classification: C23, G01, J23, J29, J69
PIDS FOR CONGESTION CONTROL IN INTERNET USING OPNET

This paper presents some simulation-based examples used at graduate level, so that engineering students understand the problems caused by congestion in computer networks, and some possible solutions. This is a necessity, as fast and reliable computer links are needed, but there are situations when congestion happens in those links, caused by fluctuations in the network delay and the number of users. The methodology presented here allows students to learn the importance of the Quality of Service (QoS) and how it depends on the methods used to solve the congestion problem. This work presents a combined approach of ready and selfprogrammed methods combined with tutorials using OPNET and MATLAB. Different approaches for dealing with congestion are considered: Drop Tail, RED and PIDs.
MDS-based Algorithm for Nodes Localization in 3 D Surface Sensor Networks

As Wireless Sensor Network (WSN) has become a key technology for different types of smart environment, nodes localization in WSN has arisen as a very challengin g problem in the research community. Most of the applications for WSNs necessitate a priory known nodes positions. In this paper, we propose an algorithm for three dimensional (3D) nod es localization in surface WSN based on multidimension al scaling (MDS) technique. Using extensive simulations, we in vestigated in details our approach regarding different network topologies, various network parameters and performance issues. The results from simulations show that our algorithm produces small localization error and outperforms MDS-MAP in terms of accuracy. Keywords-wireless sensor networks; multidimensional scaling; 3D surface localization; nodes positioning.
Antioxidant activity and phenol content of extracts of bark , stems , and young and mature leaves from Blepharocalyx salicifolius ( Kunth ) O .

Phenolic compounds are a group of plant secondary metabolites known to have a variety of bioactivities, including the ability to function as antioxidants. Because of the side effects of the use of synthetic substances, the search for natural and less toxic compounds has increased significantly. This study was designed to evaluate the antioxidant activity and phenol content of hexane, ethyl acetate, and aqueous extracts of the bark (suber) and stems as well as the young and mature leaves of Blepharocalyx salicifolius. The extracts were obtained by extraction with organic solvents and subsequent fractionation by chromatographic partition coefficient. Preliminary tests for the presence of antioxidants were performed using bioautography in thin-layer chromatography. The antioxidant activity of the extracts was assessed using the 2,2-diphenyl-1-picrylhydrazyl (DPPH) method, and the phenol content of the extracts was quantified using the Folin-Ciocalteu technique. The results showed that 9 of the 12 extracts evaluated displayed very strong antioxidant activity and three displayed moderate activity. Aqueous extracts of the young leaves and bark and the ethyl acetate extract of the young leaves showed the highest levels of antioxidant activity and total phenolic content (TPC). A correlation was observed between TPC and antioxidant activity index (AAI) with a correlation coefficient (r2) of 0.7999. Thus, the high phenol content of B. salicifolius extracts and its correlation with antioxidant activity provide substrates for further studies.
INTERACTION BETWEEN PEDESTRIANS AND THEIR ENVIRONMENT WHEN ROAD-CROSSING: A BEHAVIOURAL APPROACH

The significant number of injured pedestrians shows their vulnerability in front of vehicles. From the driver's point of view, pedestrians are slow, fragile, and with unexpected behaviour; their movements can abruptly change direction (sides, step backward). Moreover, their caution in the perception of the environment is sometimes limited. After a brief state of the art in the simulation of the pedestrians including various connected problems, we will present a solution we have adopted and implemented within the behavioural traffic simulation model ARCHISIM. We will explain how our work is directly influenced by psychological findings related to human behaviour. Then we will give first results in term of impact of the infrastructure management on both pedestrian and vehicle flows, for concluding on future developments.