Miracle-dz/UniFAR-FTUs huggingface dataset:
SHERPA HS-STEM Internship

August 2005, hurricane Katrina smashes into New Orleans and the surrounding areas. At a cost of over 1,800 lives and $160 billion, this tragedy caused a great loss for the United States [1]. There is a lot of speculation to be made about what occurred, and how any damages could have been mitigated; however, Katrina gave us a clear message: our emergency planning system is insufficient. Messages like Katrina and 9-11 are the calls SHERPA hopes to answer. This software leverages a previous modeling project entitled Standard Unified Modeling and Mapping Integration Toolkit (SUMMIT), to prepare and plan for homeland emergencies. Resulting in the name: SUMMIT for Homeland Emergency Response & Planning Analysis (SHERPA). SUMMIT allows the use of a large library of models for various situations: chemical tanker explosions, earthquakes, hurricanes, and many more scenarios. It also possesses the capability to interface with any other software/models (hereafter referred to as “wrapping”)
Something New Under The Sun : Thoughts on Optimizing the Performance of Blockchains Zsolt

Blockchains (distributed ledgers) are often used synonymously with crypto-currencies and UTXO data models, such as that of Bitcoin, but there are emerging blockchain platforms that offer a more general data model and smart contracts that can manipulate data freely (e.g. Ethereum [22], Tezos [9] and Hyperledger Fabric [1]). As such, these platforms resemble in many ways distributed databases, storing a collection of records (key-value pairs) on the ledger that smart contracts can access and modify. Blockchains are also generally seen as sluggish, e.g., Bitcoin transactions reach committed state only after several minutes. Their high latency and low throughput is mainly due to the reliance on proof of work-based (PoW) consensus mechanisms [13], where the participants have to solve a cryptographic puzzle before they are allowed to construct a block of the blockchain (also called mining). This means that the performance of these systems if tightly coupled with the mining speed. As a result, blockchains have not been a good target for hardware acceleration when it comes to their core infrastructure, since PoW dominates most costs. Luckily, not all blockchains use PoW consensus. Permissioned distributed ledgers, for instance, rely on a third party to authenticate nodes (i.e., give permission to access the ledger) and then use more traditional consensus algorithms among participants. Examples of such systems include Hyperledger Fabric [1] and Corda [3]. A common use case for these systems is, for instance, in supply chain management [18, 17], where participating companies rely on the distributed ledger as a tamper-free method of recording transactions and executing smart contracts. Furthermore, storing all data in a common system enables valuable insights into the inefficiencies of the supply chain [18]. Surprisingly, permissioned ledgers are also slow. This is because they inherit their core design from public blockchains and, as a result, their latencies are typically in the order of half a second, even when running on a local area network. In these settings, the high latency of committing operations can hinder wide-spread adoption, especially given that these systems do not require costly proof-of-work, and the fundamental problem distributed ledgers solve, namely reaching consensus among nodes, can be performed at the order of milliseconds even if we assume Byzantine faults [2, 5].
Exploring Micro-Movements for Diagnostics of Neurological Problems

Tremor can be as a symptom of such neurological diseases as Parkinson's disease, multiple sclerosis, and damage to the cerebellum. A successful screening method could open the way for earlier treatment that may delay the progression of presently incurable diseases. The goal of this project was an exploration of the pen-based technique for early diagnostics of the deterioration level in a person’s ability to control micro-movements. Eight subjects of different age groups took part in the pilot test. The method was based on a comparison of the personal immediate handwriting performance in copying the graphical patterns. The performance of the subjects in game-like testing was evaluated in terms of the stylus deviation and correlation of the scan path to the graph on X-axis and Y-axis separately and the task completion time when output-to-input ratio was non-less than 4. The results of a pilot testing are analyzed. They reveal that coordination problems can be registered even when the problems have not previously been detected by the person himself. We guess that further exploration of the penbased technique for screening hand-eye coordination problems can increase selective sensitivity of the method regarding verified symptoms of neurological problems. Author Keywords
Pterogyne nitens Genetic variation among and within populations of the amendoim-Pterogyne nitens

The genetic variation among and within populations of Pterogyne nitens Tul. was studied on the height and the BHD traits, evaluated from 5 to 15 years old. The progeny trial was planted at Experimental Station in Pederneiras SP in the compact family blocks design. The F test did not revealed significant genetic differences among populations, for both characteristics. However, for progenies within populations, these values were highly significant, showing high genetic variation among families within populations. This is according to the behavior of another tropical arboreal species, evaluated initially from quantitative characters and isozymes analysis. The survival plants were of the 89,58% (5 years) and 62,22% (15 years) and wich combined with the average growth and annual average increments for BHD and height show that the species is SCIENTIA FORESTALIS n. 56, p. 29-40, dez. 1999 Variação genética entre e dentro de populações de amendoim Pterogyne nitens Genetic variation among and within populations of the amendoim Pterogyne nitens Alexandre Magno Sebbenn Ana Cristina Machado de Franco Siqueira Paulo Yoshio Kageyama Omar Jorge di Dio Junior 30 n Variação genética em amendoim not well adjusted for pure plantation, being ideal in the case the consorciation with pioneer species. The coefficient of genetic variation among progenies, heritability and the coefficient of phenotipic variation within progenies were expressives for characteristics, revealed the genetic material as highly potential for ex situ conservation and improvement programs.
Interactive Virtual Reality Real-Time Avatar for Military Rehabilitation in the Canadian Forces Major ( Professor )

Major (Professor) Luc J. Hébert, PT, PhD, CD Canadian Forces Health Services Headquarters, Directorate of Medical Policy (Physiotherapy) Valcartier Garrison, 5 Field Amb, CSV (B-109; room #2006), CP 1000, Succ. FORCES Quebec City, Quebec, GOA 4ZO and Centre for Research in Rehabilitation and Social Integration (CIRRIS), and Department of Radiology, Laval University, Quebec City. Quebec, Canada luc.hebert@forces.gc. ca, ljhebert@videotron.ca
Using Language to Predict Kickstarter Success

Kickstarter is a popular crowdfunding platform that is used by people to seek support on a variety of campaigns. Existing literature has already tackled the problem of predicting campaign success (meeting the funding target by the deadline), typically analyzing the evolution of a campaign’s funding and number of backers over time to predict its success. While time-dependent features are effective in predicting success, especially as a campaign nears its deadline, we took a different approach to the problem and built a binary classifier that predicts the success of a campaign by analyzing campaign content, linguistic features, and meta-information at the time of its inception (through techniques such as sentiment analysis and latent Dirichlet allocation). With sufficient training, our classifier achieves over 70% accuracy on large test data sets. We show that language and campaign properties alone can be used to make moderate predictions about the success of a campaign, which helps us understand how the subtleties of persuasion and the choice of campaign topics can influence campaign donors and informs the process of evaluating and developing effective campaign pitches.
Effect of Teaching Goals Program on Selecting Instructional Methods Used by Nursing Faculty Staff

Background: Excellent and effective teaching, first of all, gains the students' attention and convinces them of the importance of what is being taught and learned. It goes on to communicate not only information and concepts but to develop powers of analysis, synthesis, judgment, and evaluation, all in a context of considered values. When teaching has truly succeeded, students leave with an ability to learn, question, and commit on their own. To achieve that, the teachers need to be aware enough of the teaching goals which enhanced the selection of appropriate teaching strategy. The purpose: The aim of the present study was to examine the effect of teaching goals program on selecting instructional methods used by academic staff members teaching in nursing faculty. Methods: It is conducted at Faculty of Nursing-Mansoura University-Delta Region. All academic staff members (n=21) working at Nursing Faculty participated in this study. Two tools were used in this study, the first tool named instructional methods questionnaire sheet. The aim of this sheet was to identify the instructional methods used by each academic staff member teaching in nursing faculty. The second tool was multiple choice questions. It was aimed to measure the knowledge and attitude of academic staff members related to teaching goals. Results: The major findings of this study indicated that although there was statistical significant difference between the academic staff knowledge regarding teaching goals before and after the program, it is explored no statistical significant difference in their selection of instructional methods before, immediate post and after three months of the teaching goals program. Conclusion: this study concluded that the improvement in academic staff knowledge regarding teaching goals was not affect on their selection of appropriate instruction methods related to their courses teaching. It was may be due to many factors out of researchers control such as resources. Recommendations: It is recommended that providing with resources such as increase the number of academic staff members to decrease the students number in each section and preparing classes with different and modern technology will give the chance to academic staff members to select the most appropriate instructional methods according to teaching goals.
ANALYSIS OF SUPER MARKET USING ASSOCIATION RULE MINING

: Supermarket analysis is a process to analyze the buyer’s habits to discover the correlations between the different items in their shopping cart. The findings of these correlations can help the retailers to establish a profitable sales strategy by considering frequently purchased items together by customers. Association rule mining is one of the famous data mining techniques used to discover the correlations between one item to another. Association rule mining technique has number of algorithms, but this research focuses on the effectiveness of the combination of the two association rule mining algorithms that are apriori algorithm and eclat algorithm for supermarket analysis. The collaboration of both the algorithms revealed that both methods use the same concept with different criteria of processing the association rules, but the rules itself remains the same.
Empowering Students and Instructors: Reflections on the Effectiveness of iPads for Teaching and Learning

At the dawn of the personal computer, it was unclear what the device would mean for teaching, learning, and personal productivity. We are seeing a similar dynamic with the rise of devices like the Apple iPad. These tablets call for purposeful experimentation to see how mobile technology might be used in teaching and learning and in updating established educational models to engage today’s students. In this ELI Brief, we describe the findings from three Indiana University (IU) faculty learning communities that spent the 2010–2011 academic year studying the effectiveness of iPads for teaching and learning.
Effect of non-genetic factors on milk fat composition: A review

Milk fat comprises of monoand polyunsaturated fatty acids; some of them are recognized to exert a beneficial effect on human health. Short and medium chain saturated fatty acids are synthesized de novo in the mammary gland while long chain fatty acid are derived from blood circulation. Milk fat is the main source of energy and natural carriers’ of triacylglycerols and bioactive molecules to the intestine of infants. They are also involved in providing the information needed for the growth of intestinal mucosa, the immune and nervous systems along with metabolic activity. They have impact on the technological and nutritional properties of the milk, hence, are important components of milk composition. The composition of milk fatty acid is affected by numerous non genetic factors such as species differences, parity or lactation order, age, size and health status of the cow, dietary composition, feeding, season, pregnancy, sire service period, lameness, heat stress, milking interval etc. Changes in milk fatty acid composition could alter nutritional and commercial values of milk as an input for dairy processing. Thus, milk fatty composition is of great importance to the dairy industry as most milk is traded as a processed
Robotics : An Academic Discipline

Position: robotics is ready to become an academic discipline in its own right, rather than an interdisciplinary field of study, where robotics is the discipline of the creation, composition, structure, evaluation, and properties of artificial (designed) embodied (physically instantiated) capabilities rather than the study of robotic systems and applications.
Automatic transcription of the melody from polyphonic music

This dissertation addresses the problem of melody detection in polyphonic musical audio. The proposed algorithm uses a bottom-up design, in which each module leads to a more abstract representation of the audio data, which allows a very efficient computation of the melody. Nonetheless, the dataflow is not strictly unidirectional: on several occasions, feedback from higher processing modules controls the processing of low-level modules. The spectral analysis is based on a technique for the efficient computation of short-time Fourier spectra in different time-frequency resolutions. The pitch determination algorithm (PDA) is based on the pair-wise analysis of spectral peaks. Although melody detection implies a strong focus on the predominant voice, the proposed tone processing module aims at extracting multiple fundamental frequencies (F0). In order to identify the melody, the best succession of tones has to be chosen. This thesis describes an efficient computational method for auditory stream segregation that processes a variable number of simultaneous voices. The presented melody extraction algorithm has been evaluated during the MIREX audio melody extraction task. The MIREX results show that the proposed algorithm belongs to the state-of-the-art-algorithms, reaching the best overall accuracy in MIREX 2014.
Information-Based Multi-Fidelity Bayesian Optimization

This paper presents a novel generalization of predictive entropy search (PES) for multi-fidelity Bayesian optimization (BO) called multi-fidelity PES (MF-PES). In contrast to existing multi-fidelity BO algorithms, our proposed MF-PES algorithm can naturally trade off between exploitation vs. exploration over the target and auxiliary functions with varying fidelities without needing to manually tune any such parameters or input discretization. To achieve this, we first model the unknown target and auxiliary functions jointly as a convolved multi-output Gaussian process (CMOGP) whose convolutional structure is then exploited for deriving an efficient approximation of MF-PES. Empirical evaluation on synthetic and real-world experiments shows that MF-PES outperforms the state-of-the-art multi-fidelity BO algorithms.
Environmental and economic assessment of agricultural production practices at a regional level based on uncertain knowledge

The concept of sustainability and international trade relations require changes in the current agrienvironmental policy of the European Community. Therefore, in the future, the EU funded agricultural subsidies will increasingly be linked to the environmental performance of agricultural practices. To develop an effective agro-environmental policy, tools are needed that allow detailed economic and environmental analysis of different policy options. At the same time there is often only limited knowledge about the complex interdependencies between the different forms of agricultural land use and the related effects on the environment and landscape functions. The aim of this paper is to introduce a fuzzy-logic-based approach, which is tolerant of uncertain knowledge, to evaluate agricultural production practices regarding their effects on different abiotic and biotic environmental indicators on a regional scale refering to a modeled region of 200 km2 in the northeast of Germany.
Detekce dopravnı́ch značek v obraze a videu

Abstrakt Tato práce řešı́ problematiku detekce dopravnı́ho značenı́ za pomoci modernı́ch technik zpracovánı́ obrazu. K řešenı́ byla použita speciálnı́ architektura hluboké konvolučnı́ neuronové sı́tě zvaná YOLO, tedy You Only Look Once, která řešı́ detekci i klasifikaci objektů v jednom kroce, což celý proces značně urychluje. Práce pojednává také o porovnánı́ úspěšnosti modelů trénovaných na reálných a syntetických datových sadách. Podařilo se dosáhnout úspěšnosti 63.4% mAP při použitı́ modelu trénovaného na reálných datech a úspěšnosti 82.3% mAP při použitı́ modelu trénovaného na datech syntetických. Vyhodnocenı́ jednoho snı́mku trvá na průměrně výkonném grafickém čipu ∼40.4ms a na nadprůměrně výkonném čipu ∼3.9ms. Přı́nosem této práce je skutečnost, že model neuronové sı́tě trénovaný na syntetických datech může za určitých podmı́nek dosahovat podobných či lepšı́ch výsledků, než model trénovaný na reálných datech. To může usnadnit proces tvorby detektoru o nutnost anotovat velké množstvı́ obrázků. Klı́čová slova: Konvolučnı́ neuronová sı́t’ — YOLO — Detekce — Syntetická — Dopravnı́ značka Přiložené materiály: Demonstračnı́ video — Generátor datových sad
nhancing the quantity and accuracy of eyewitness memory via initial emory testing

Previous studies have demonstrated the benefits of initial memory testing in terms of “inoculating” eyewitness memory against forgetting. The aim of the present study was to determine to what extent and under which conditions such testing may also enhance the accuracy of subsequent retrieval. Two aspects of interpolated testing were manipulated: the mode of interpolated testing (forced verbatim vs. free level) and its timing (immediate vs. delayed). After witnessing a target event, participants were questioned about event details either immediately or after a 48-h delay, and were either required to respond at the verbatim level or were given control over the grain size of their responses. Verbatim memory for event details was finally tested 72 h after the event under both standard forced-report conditions and
Project-Based Learning Practices with Secondary School Students 1

Article History: Received 13.11. 2017 Received in revised form 02.04. 2018 Accepted 30.05. 2018 Available online 14.05. 2018 Aiming to identify academic self-efficacy and academic motivations to middle school students by providing them opportunities to conduct and present their own projects in accordance with their interests and skills, this study covers the consequence assessment obtained from the second term of the TÜBİTAK-supported research project ‘‘Kafkasın Mucitleri Bilimle Buluşuyor (Caucasian Inventors Meet with Science)’’, and the comparison of this assessment with the results attained from the first term of the project. The study group consists of 39 middle school students from 7th grade who volunteered to participate in the study in Kars province center. As data collection tool, the "Academic Self-Efficacy Scale" and "Academic Motivation Scale" were used. In this research where the one group pre-test-post-test design was used, academic self-efficacy and academic motivation scales were implemented as pre-test and post-test. As a result of the research, it has been determined that there was no change in confidence of the students regarding their own skills or the school environment they were present. When the Academic Motivation levels of the students were evaluated, it has been determined that there was only a change in their introjected extrinsic motivation levels. © 2018 IOJES. All rights reserved
Investigation resence of Iberian wolf ( Canis lupus signatus ) in relation to land cover , ivestock and human influence in Portugal

From June 2005 to March 2007, we investigated wolf presence in an area of 1000 km2 in central northern Portugal by scat surveys along line transects. We aimed at predicting wolf presence by developing a habitat model using land cover classes, livestock density and human influence (e.g. population and road density). We confirmed the presence of three wolf packs by kernel density distribution analysis of
Influence of the low temperature on the mechanical guided waves in aluminium sheets

Using the mechanical guided waves is well known for online and offline detection and localization of the structural defects. The environmental parameters could have a significant influence on the performances parameters of the testing method. An important environmental parameter which could influence the testing method performances is the temperature. It affects all the measurement system components from wave generation to signal acquisition. The temperature can affect the most sensitive components of the measurement system such as the piezoelectric actuators and transducers and the mechanical coupling material between them and the monitored structure. For establishing how big this influence is on the whole system we have performed an experimental laboratory work using as piezoelectric actuators and transducers PWAS (Piezo-electric Wafers Active Sensors) glued to an aluminium plate structure. The PWAS has been used both way as receiver and transmitter for the mechanical guided waves. The experiment has been performed for few wave frequencies such as S0 and A0 dominant frequencies and few other values and for -70 – 00C temperature range. The received signal amplitude shows important changes with temperature. This is an important aspect which needs to be considered for optimizing the structural health monitoring method.
Antifeedant activity of flavonoids and related compounds against the subterranean termite Coptotermes formosanus

Antifeedant activity of some flavonoids and their related compounds against the subterranean termite Coptotermes formosanus Shiraki was examined with nochoice tests and two-choice tests. The activities of these compounds were evaluated in relation to their chemical structures. All flavonoids tested showed antifeedant activity, whereas catechinic acid, possessing no A-ring or pyran ring in the molecule, showed feeding-preference activity. For the structure-activity relations, it was found that compounds containing two hydroxyl groups at C-5 and C-7 in A-rings showed high antifeedant activity. Furthermore, the presence of a carbonyl group at C-4 in the pyran rings of the compounds was necessary for the occurrence of high activity. 3-Hydroxyflavones and 3-hydroxyflavanones with 3' ,4 'dihydroxylated B-rings exhibited higher activity than those with 4 ' -hydroxylated B-rings.