Miracle-dz/UniFAR-FTUs huggingface dataset:
Deep Learning for Forest Species Identification Based on Macroscopic Images

The fast and accurate identification of forest species is critical to support their sustainable management, to combat illegal logging, and ultimately to conserve them. Traditionally, the anatomical identification of forest species is a manual process that requires a human expert with a high level of knowledge to observe and differentiate certain anatomical structures present in a wood sample (Wiedenhoeft (2011)). In recent years, deep learning techniques have drastically improved the state of the art in many areas such as speech recognition, visual object recognition, and image and music information retrieval, among others (LeCun et al. (2015)). In the context of the automatic identification of plants, these techniques have recently been applied with great success (Carranza-Rojas et al. (2017)) and even mobile apps such as Pl@ntNet have been developed to identify a species from images captured on-the-fly (Joly et al. (2014)). In contrast to conventional machine learning techniques, deep learning techniques extract and learn by themselves the relevant features from large datasets. One of the main limitations for the application of deep learning techniques to forest species identification is the lack of comprehensive datasets for the training and testing of convolutional neural network (CNN) models. For this work, we used a dataset developed at the Federal University of Parana (UFPR) in Curitiba, Brazil, that comprises 2939 images in JPG format without compression and a resolution of 3.264 x 2.448 pixels. It includes 41 ‡ ‡ ‡ ‡ © Mata-Montero E et al. This is an open access article distributed under the terms of the Creative Commons Attribution License (CC BY 4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. different forest species of the Brazilian flora that were cataloged by the Laboratory of Wood Anatomy at UFPR (Paula Filho et al. (2014)). Due to the lack of comprehensive datasets world wide, this has become a benchmark dataset in previous research (Paula Filho et al. (2014), Hafemann et al. (2014)). In this work, we propose and demonstrate the power of deep CNNs to identify forest species based on macroscopic images. We use a pre-trained model which is built from the resnet50 model and uses weights pre-trained on ImageNet. We apply fine-tuning by first truncating the top layer (softmax layer) of the pre-trained network and replacing it with a new softmax layer. Then we train again the model with the dataset of macroscopic images of species of the Brazilian flora used in (Hafemann et al. (2014), Paula Filho et al. (2014)). Using the proposed model we achieve a top-1 98% accuracy which is better than the 95.77% reported in (Hafemann et al. (2014) )using the same data set. In addition, our result is slightly better than the reported in (Paula Filho et al. (2014)) of 97.77% which was obtained by combining several conventional techniques of computer vision.
Analysing interlanguage: how do we know what learners know?

In this article, we address the important issue of ‘how we know what learners know’ based on evidence from second language (L2) learners’ spontaneous speech samples gathered longitudinally. We first examine some of the problems involved in the analysis of spontaneous speech, with focus on L2 studies within the generative framework. Next, we revisit the issue of the comparative fallacy in L2 research. We first consider the effects of the comparative fallacy in relation to analyses of interlanguage with a target language bias. Next, we extend the comparative fallacy to include interlanguage analysis where the bias is towards the native language. We argue that the comparative fallacy in interlanguage studies, regardless of the nature of the bias (i.e., target language or native language) can lead to the underestimation and/or overestimation of the learners’ linguistic competence.
Practices to Reduce Milk Carbon Footprint on Grazing Dairy Farms in Southern Uruguay: Case Studies

Carbon footprint (CF) is an increasingly important indicator of the impact of a product on climate change. This study followed international guidelines to quantify the CF of milk produced on 24 grazing-based dairy farms in southern Uruguay. Cows grazed all year-round and were supplemented with concentrate feeds. Dairy farms varied in annual milk yield per cow (5672 ± 1245 kg fat and protein corrected milk [FPCM]), milk production per ha (4075 ± 1360 kg FPCM/ha), cow stocking rate (0.71 ± 0.12 cows/ha), feed intake (13.3 ± 2.2 kg dry matter [DM]/cow/day) and percentage of concentrate in the diet (36 ± 12% DM) giving an average CF of 0.99 ± 0.10 kg CO2 (equivalent [eq]/kg FPCM) over all farms. Total milk production per ha, milk yield per cow and dry matter intake explained most of the variation in CF. Strategies that provide the highest milk production per ha using high yielding cows and a high portion of lactating cows in the herd were identified as the best management practices for reducing CF. Low forage intake in Uruguay is often a consequence of low yielding pastures and high stocking rates. Overall, this study concluded that a reduction in CF is not achieved through increased concentrate intake unless forage consumption is also unconstrained. Improved pasture and feeding management can be used to reduce the CF of milk produced in Uruguay.
Chiral drag force Citation Rajagopal

We provide a holographic evaluation of novel contributions to the drag force acting on a heavy quark moving through strongly interacting plasma. The new contributions are chiral in the sense that they act in opposite directions in plasmas containing an excess of leftor right-handed quarks. The new contributions are proportional to the coefficient of the axial anomaly, and in this sense also are chiral. These new contributions to the drag force act either parallel to or antiparallel to an external magnetic field or to the vorticity of the fluid plasma. In all these respects, these contributions to the drag force felt by a heavy quark are analogous to the chiral magnetic effect (CME) on light quarks. However, the new contribution to the drag force is independent of the electric charge of the heavy quark and is the same for heavy quarks and antiquarks, meaning that these novel effects do not in fact contribute to the CME current. We show that although the chiral drag force can be non-vanishing for heavy quarks that are at rest in the local fluid rest frame, it does vanish for heavy quarks that are at rest in a suitably chosen frame. In this frame, the heavy quark at rest sees counterpropagating momentum and charge currents, both proportional to the axial anomaly coefficient, but feels no drag force. This provides strong concrete evidence for the absence of dissipation in chiral transport, something that has been predicted previously via consideration of symmetries. Along the way to our principal results, we provide a general calculation of the corrections to the drag force due to the presence of gradients in the flowing fluid in the presence of a nonzero chemical potential. We close with a consequence of our result that is at least in principle observable in heavy ion collisions, namely an anticorrelation between the direction of the CME current for light quarks in a given event and the direction of the kick given to the momentum of all the heavy quarks and antiquarks in that event.
LongMemory of Pathfinding Aesthetics

This paper investigates a new dynamic (i.e., space-time) model to measure aesthetic values in pathfinding for videogames. The results we report are important firstly because the artificial intelligence literature has given relatively little attention to aesthetic considerations in pathfinding. Secondly, those investigators who have studied aesthetics in pathfinding have relied largely on anecdotal arguments rather than metrics. Finally, in those cases where metrics have been used in the past, they show only that aesthetic paths are different. They provide no quantitative means to classify aesthetic outcomes. The model we develop here overcomes these deficiencies using rescaled range (R/S) analysis to estimate the Hurst exponent, H . It measures longrange dependence (i.e., long memory) in stochastic processes and provides a novel well-defined mathematical classification for pathfinding. Indeed, the data indicates that aesthetic and control paths have statistically significantly distinct H signatures. Aesthetic paths furthermore have more long memory than controls with an effect size that is large, more than three times that of an alternative approach. These conclusions will be of interest to researchers investigating games as well as other forms of entertainment, simulation, and in general nonshortest path motion planning.
The Parametric Aircraft Noise Analysis Module - status overview and recent applications

The German Aerospace Center (DLR) is investigating aircraft noise prediction and noise reduction capabilities. The Parametric Aircraft Noise Analysis Module (PANAM) is a fast prediction tool by the DLR Institute of Aerodynamics and Flow Technology to address overall aircraft noise. It was initially developed to (1) enable comparative design studies with respect to overall aircraft ground noise and to (2) indentify promising low-noise technologies at early aircraft design stages. A brief survey of available and established fast noise prediction codes is provided in order to rank and classify PANAM among existing tools. PANAM predicts aircraft noise generated during arbitrary 3D approach and take-off flight procedures. Noise generation of an operating aircraft is determined by its design, the relative observer position, configuration settings, and operating condition along the flight path. Feasible noise analysis requires a detailed simulation of all these dominating effects. Major aircraft noise components are simulated with individual models and interactions are neglected. Each component is simulated with a separate semi-empirical and parametric noise source model. These models capture major physical effects and correlations yet allow for fast and accurate noise prediction. Sound propagation and convection effects are applied to the emitting noise source in order to transfer static emission into aircraft ground noise impact with respect to the actual flight operating conditions. Recent developments and process interfaces are presented and prediction results are compared with experimental data recorded during DLR flyover noise campaigns with an Airbus A319 (2006), a VFW-614 (2009), and a Boeing B737-700 (2010). Overall, dominating airframe and engine noise sources are adequately modeled and overall aircraft ground noise levels can sufficiently be predicted. The paper concludes with a brief overview on current code applications towards selected noise reduction technologies.
Estimation of Radiation Dosimetry for some Common SPECT-CT Exams

Single photon emission computed tomography associated to X ray computed tomography (SPECT-CT) is a nuclear medicine tomographic imaging technique which improves diagnostic accuracy for particular clinical indications due to the possible attenuation and/or scatter correction of the SPECT functional images and the availability of helpful anatomic information. However, the introduction of CT in the nuclear diagnostic process results in a significant increase of the patient dose. Ideally is to establish sufficient image quality for a specific diagnostic task with the lowest effective dose to the patient in order to reduce stochastic effects. Indication of SPECT-CT should be made to adhere to the “As Low as Reasonably Achievable (ALARA)” principle and ensure that the patient is not subjected to unnecessarily high levels of radiation. In this study, we evaluate effective doses received during some standard nuclear medicine exams from 100 patients who underwent SPECT-CT in our department and analyze parameters involved in variation of these doses according to the literature data.
Developing a Framework of Islamic Bank Operational Risk Management: ‘People Risk’

ABSTRACT The study of human resource has become a crucial topic in understanding the determinants of operational risk. Given the various sources of operational risk, losses resulting from staff performance seemed to be the major cause as employees are the key players who manage the processes and systems of undesired events. This study explored the influence of staff performance attributes toward operational risk management, with a focus on ‘people risk’. The study was conducted using qualitative approach via face-to-face and telephone interviews with 14 respondents from 7 Islamic banks in Malaysia. Our preliminary finding showed that training, education, experience and compensation lead toward better management of ‘people risk’. Hence, a clear understanding of the factors affecting ‘people risk’ would help ensuring an effective and successful strategy in managing human resources especially in developing the operational risk management framework for the Islamic banking institutions. Keywords: Islamic banking institutions; operational risk management; staff performance ABSTRAK Kajian berkaitan sumber manusia telah menjadi topik penting untuk memahami faktor penentu risiko operasi. Walaupun risiko operasi berpunca daripada pelbagai sumber, kerugian akibat daripada tahap prestasi pekerja yang rendah menjadi punca utama disebabkan pekerja memainkan peranan penting dalam menguruskan aliran proses dan sistem bagi sesebuah institusi terhadap peristiwa yang tidak diingini. Kajian ini meneroka faktor-faktor yang mempengaruhi prestasi pekerja dalam konteks pengurusan risiko operasi dengan penumpuan kepada 'risiko pekerja’. Kajian ini menggunakan pendekatan kualitatif melalui temubual secara bersemuaka dan telefon terhadap 14 responden yang terdiri daripada 7 buah institusi perbankan Islam di Malaysia. Penemuan awal kajian ini menunjukkan bahawa latihan, pendidikan, pengalaman dan ganjaran mendorong kepada pengurusan ‘risiko pekerja’ yang lebih baik. Oleh itu, kefahaman yang jelas terhadap faktor-faktor yang mempengaruhi 'risiko pekerja' membantu dalam merangka strategi yang efektif bagi pengurusan sumber manusia terutamanya dalam membangunkan rangka kerja pengurusan risiko operasi bagi institusi perbankan Islam. Kata kunci: Institusi perbankan Islam; pengurusan risiko operasi; prestasi pekerja
Refining error estimates for a millennial temperature reconstruction

Abstract. The statistical uncertainties in a 1000 year Northern Hemisphere mean temperature reconstruction obtained from 15 proxy chronologies are examined in detail by analysing the range of estimates obtained from all possible subsets of the proxy collection with up to 6 proxies omitted. The study is motivated in part by the large range of recently published reconstructions in the 15th and 16th centuries. The uncertainty estimates support the conclusions of the 3rd and 4th Intergovernmental Panel on Climate Change (IPCC) assessment reports concerning the likelihood that temperatures at the end of the 20th century were likely (greater than 66% confidence) to have been exceptional. It is also shown that the last ten years to date have been warmer than any decade of the past millennium with 95% confidence.
The Triple Flip: Using Technology for Peer and Self-Editing of Writing.

Many teachers consider themselves digital immigrants who struggle to keep up with student digital natives. Whether or not this dichotomy still holds true, in a 21st Century context of teaching and learning, is debatable not least of all because of the exponential development of apps and mobile learning technology. Nevertheless, it is sometimes difficult for educators to know where to begin and for students to know how best to use it to advance their studies and improve their writing. Focusing on university students at a pre-university English as Second Language (ESL) program in Dubai, this paper discusses how mobile learning and the use of a range of apps can foster peer and self-editing, aid noticing and enhance ownership of the writing process. It is argued that flipping corrective feedback helps students to notice their errors and spend more time developing their writing.
HBCU Students' Perceptions of Their Readiness for College Composition

A vast majority of sources examining Historically Black Colleges and Universities (HBCUs) limit their discussion to the relatively low performance, low economic status, and low graduation rates of students at such universities. Research focusing on the voices of students in general is scarce especially, when it comes to students at HBCUs. This study is designed to examine the student’s experiences in grades 9 – 12 and their readiness for college composition. Providing students with a voice in their learning experiences could help in the attempt to increase graduation rates at HBCUs, especially if students are treated as though they are the experts in their experiences. This study examined the students’ perceptions of their abilities and their actual performance. Most of the students explained that they were adequately prepared. All except one of the students expressed their readiness English at the college. Although most of the students passed freshman composition, they did not gain some of the skills required in college. The study revealed that high school teachers place different degrees of importance on some skills. A lack of connection between high school English courses and college English classes exists. The students contended that they would have liked for the assignments given in highs schools to be more similar to those assigned in college. Thus, collaboration between high school teachers and university professors could have decreased the fear that some students faced when they first enter college.
Relationship between performance appraisal communication, procedural justice and job satisfaction

Performance appraisal communication is a segment of performance appraisal management denoting the process of sharing and transferring appraisal information from appraiser to appraisee either face-to-face or through technical and communication gadgets. The traditional performance appraisal was based on past performance of the employees, single-source feedback, non-participation style in decision making and boss-centred approach. It did not consider the development aspects of the employee performance as it was preoccupied with judging the performance of the organization as a whole. To address the drawback of this approach, modern approaches were introduced in the era of globalization which centred on humanistic perspectives, system thinking and contingency views. In the light of the new approaches, this paper examines the effect of performance appraisal communication and procedural justice on job satisfaction using 99 usable questionnaires collected from employees who work at public tertiary educational institutions in East Malaysia. The outcomes of stepwise regression analysis showed that relationship between feedback, treatment and procedural justice significantly correlated with job satisfaction. In sum, this result demonstrates that the ability of appraisers to appropriately provide feedback and treatment will strongly invoke appraisees’ feelings of procedural justice and this may lead to an enhanced job satisfaction in the organization studied. Keywords: appraisees’ feelings, employee feedback, employee performance, job satisfaction, performance appraisal communication, procedural justice
Inborn Errors of EnergyMetabolism Associated withMyopathies

Inherited neuromuscular disorders affect approximately one in 3,500 children. Structural muscular defects are most common; however functional impairment of skeletal and cardiac muscle in both children and adults may be caused by inborn errors of energy metabolism as well. Patients suffering from metabolic myopathies due to compromised energy metabolism may present with exercise intolerance, muscle pain, reversible or progressive muscle weakness, and myoglobinuria. In this review, the physiology of energy metabolism in muscle is described, followed by the presentation of distinct disorders affecting skeletal and cardiac muscle: glycogen storage diseases types III, V, VII, fatty acid oxidation defects, and respiratory chain defects (i.e., mitochondriopathies). The diagnostic work-up and therapeutic options in these disorders are discussed.
Groups and clusters of galaxies in the SDSS DR8 - Value-added catalogues

Aims. We intend to compile a new galaxy group and cluster sample of the latest available SDSS data, adding several parameter for the purpose of studying the supercluster network, galaxy and group evolution, and their connection to the surrounding environment. Methods. We used a modified friends-of-friends (FoF) method with a variable linking length in the transverse and radial directions to eliminate selection effects and to find reliably as many groups as possible. Using the galaxies as a basis, we calculated the luminosity density field. Results. We create a new catalogue of groups and clusters for the SDSS data release 8 sample. We find and add environmental parameters to our catalogue, together with other galaxy parameters (e.g., morphology), missing from our previous catalogues. We take into account various selection effects caused by a magnitude limited galaxy sample. Our final sample contains 576493 galaxies and 77858 groups. The group catalogue is available at this http URL and from the Strasbourg Astronomical Data Center (CDS).
Antioxidant activity and storage regime of defatted grape seeds flour

In the present paper, we examined the antioxidant activity of a defatted grape seeds flour of different grape varieties locally grown in Bulgaria. The seeds are retrieved after alcoholic fermentation and the antioxidant activity of the flour was assessed by using four different methods, namely DPPH, ABTS, FRAP and CUPRAC. The results are presented in mM TE/g extract. The values are 586,08 (±41,55); 945,41 (±90,97); 553,39 (±45,57) and 667,73 (±64,30), respectively. The results are also showed in mM TE/g flour. The values are 58,67 (±4,16); 94,64 (±9,11); 55,40 (±4,56) and 66,85 (±6,44), respectively. During three-month storage of the flour in plastic bags (temperature 25 ºC and relative humidity 75%), no living cells of pathogenic organisms (Escherichia coli, Staphylococcus aureus and Salmonella spp.) or apparent molding were detected. The flour particle size has not changed either.