Miracle-dz/UniFAR-FTUs huggingface dataset:
Biogeosciences An integrated model of soil-canopy spectral radiances , photosynthesis , fluorescence , temperature and energy balance

This paper presents the model SCOPE (Soil Canopy Observation, Photochemistry and Energy fluxes), which is a vertical (1-D) integrated radiative transfer and energy balance model. The model links visible to thermal infrared radiance spectra (0.4 to 50 μm) as observed above the canopy to the fluxes of water, heat and carbon dioxide, as a function of vegetation structure, and the vertical profiles of temperature. Output of the model is the spectrum of outgoing radiation in the viewing direction and the turbulent heat fluxes, photosynthesis and chlorophyll fluorescence. A special routine is dedicated to the calculation of photosynthesis rate and chlorophyll fluorescence at the leaf level as a function of net radiation and leaf temperature. The fluorescence contributions from individual leaves are integrated over the canopy layer to calculate top-of-canopy fluorescence. The calculation of radiative transfer and the energy balance is fully integrated, allowing for feedback between leaf temperatures, leaf chlorophyll fluorescence and radiative fluxes. Leaf temperatures are calculated on the basis of energy balance closure. Model simulations were evaluated against observations reported in the literature and against data collected during field campaigns. These evaluations showed that SCOPE is able to reproduce realistic radiance spectra, directional radiance and energy balance fluxes. The model may be applied for the design of algorithms for the retrieval of evapotranspiration from optical and thermal earth observation data, for validation of existing methods to monitor vegetation functioning, to help interpret canopy fluorescence measurements, and to study the relationships between synoptic observations with diurnally integrated quantities. The model has been implemented in Matlab and has a modular design, thus allowing for great flexibility and scalability. Correspondence to: C. van der Tol (tol@itc.nl)
A comparison of DA white dwarf temperatures and gravities from Lyman and Balmer line studies

ABSTRACT We present measurements of the eﬀective temperatures and surface gravities fora sample of hot DA white dwarfs, using the Lyman line data available from the HUT,ORFEUSand FUSEfar-UV spacemissions. Comparingthe results with those from thestandard Balmer line technique, we ﬁnd that there is a general good overall agreementbetween the two methods. However, signiﬁcant diﬀerences are found for a number ofstars, but not always of a consistent nature in that sometimes the Balmer temperatureexceeds that derived from the Lyman lines and in other instances is lower. We concludethat, with the latest model atmosphere calculations, these discrepancies probably donot arise from an inadequate theoretical treatment of the Lyman lines but rather fromsystematic eﬀects in the observation and data reduction processes, which dominatethe statistical errors in these spectra. If these systematic data reduction eﬀects canbe adequately controlled, the Lyman line temperature and gravity measurements areconsistent with those obtained from the Balmer lines when allowance is made forreasonable observational uncertainties.Key words: stars:atmospheres – stars:white dwarfs – ultraviolet:stars.
Flying Memcache: Lessons Learned from Different Acceleration Strategies

Distributed key-value and always-in-memory store is employed by large and demanding services, such as Facebook and Amazon. It is apparent that generic implementations of such caches can not meet the needs of every application, therefore further research for optimizing or speeding up cache operations is required. In this paper, we present an incremental optimization strategy for accelerating the most popular key-value store, namely memcached. First we accelerate the computational unit by utilizing commodity GPUs, which offer a significant performance increase on the CPU-bound part of memcached, but only moderate performance increase under intensive I/O. We then proceed to improve I/O performance by replacing TCP with a fast UDP implementation in user-space. Putting it all together, GPUs for computational operations instead of CPUs, and UDP for communication instead of TCP, we are able to experimentally achieve 20 Gbps line-rate, which significantly outperforms the original implementation of memcached.
TIE: an interactive visualization of thread interleavings

Multi-core processors have become increasingly prevalent, driving a software shift toward concurrent programs which best utilize these processors. Testing and debugging concurrent programs is difficult due to the many different ways threads can interleave. One solution to testing concurrent software is to use tools, such as NASA's Java PathFinder (JPF), to explore the thread interleaving space. Although tools such as JPF provide comprehensive data about program errors, the data is generally in the form of bulk text logs, which provide little support for common analysis tasks, such as finding common and rare error states. In this paper, we present an interactive visualization tool, TIE, that integrates with JPF to enhance concurrency testing and debugging.
Design and Realization of a Novel Modular Climbing Caterpillar Using Low-Frequency Vibrating Passive Suckers

This paper presents a novel inspired modular climbing caterpillar. First, related issues such as the attachment principles and locomotion kinematics of climbing robots are summarized systematically. Based on the investigation of the movement mechanism of natural caterpillars, we combine climbing techniques with a modular approach to realize a novel prototype as a flexible wall-climbing robotic platform featuring an easy-to-build mechanical structure, a low-frequency vibrating passive attachment principle and various locomotion capabilities. The robot consists of cross-connected modules for moving. There are only two kinds of modules in the system: (i) the head and tail module, and (ii) the body module. Active joints actuated by RC servos endow the connecting modules with the ability to change shapes in two dimensions. After explaining these principles, the discussion focuses on the robot's various locomotion capabilities. Linear movements, turning movements, lateral movements, and rotating and rolling movements are achieved by an inspired control model to produce rhythmic motion. An easy-to-build modular caterpillar is designed and manufactured as an experimental prototype to confirm the feasibility of our design principle and the robot's capabilities. Finally, a conclusion is given and future work is outlined.
Influence of individual and combined healthy behaviours on successful aging

Background: Increases in life expectancy make it important to remain healthy for as long as possible. Our objective was to examine the extent to which healthy behaviours in midlife, separately and in combination, predict successful aging. Methods: We used a prospective cohort design involving 5100 men and women aged 42–63 years. Participants were free of cancer, coronary artery disease and stroke when their health behaviours were assessed in 1991–1994 as part of the Whitehall II study. We defined healthy behaviours as never smoking, moderate alcohol consumption, physical activity (≥ 2.5 h/wk moderate physical activity or ≥ 1 h/wk vigorous physical activity), and eating fruits and vegetables daily. We defined successful aging, measured over a median 16.3-year follow-up, as good cognitive, physical, respiratory and cardiovascular functioning, in addition to the absence of disability, mental health problems and chronic disease (coronary artery disease, stroke, cancer and diabetes). Results: At the end of follow-up, 549 participants had died and 953 qualified as aging successfully. Compared with participants who engaged in no healthy behaviours, participants engaging in all 4 healthy behaviours had 3.3 times greater odds of successful aging (95% confidence interval [CI] 2.1–5.1). The association with successful aging was linear, with the odds ratio (OR) per increment of healthy behaviour being 1.3 (95% CI 1.2–1.4; population-attributable risk for 1–4 v. 0 healthy behaviours 47%). When missing data were considered in the analysis, the results were similar to those of our main analysis. Interpretation: Although individual healthy behaviours are moderately associated with successful aging, their combined impact is substantial. We did not investigate the mechanisms underlying these associations, but we saw clear evidence of the importance of healthy behaviours for successful aging.
Predicting Interest: Another Use for Latent Semantic Analysis

Latent Semantic Analysis (LSA) is a statistical technique for extracting semantic information from text corpora. LSA has been used with success to automatically grade student essays (Intelligent Essay Scoring), model human language learning, and model language comprehension. We examine how LSA may help to predict a reader’s interest in a selection of news articles, based on their reported interest for other articles. The initial results are encouraging. LSA (using default corpus and setup) can closely match human preferences, with RMSE values as low as 2.09 (human ratings being on a scale of 1-10). Additionally, an Adapting Measure (best parameters for each individual) produced significantly better results, RMSE = 1.79.
Corpus-based synthesis of fundamental frequency contours with various speaking styles from text using F0 contour generation process model

A corpus-based method of generating fundamental frequency (F0) contours of various speaking styles from text was developed. Instead of directly predicting F0 values, the method predicts command values of the F0 contour generation process model. Because of the model constraint, the resulting F0 contour keeps certain naturalness even when the prediction is done incorrectly. The method includes a scheme of automatic extraction of the model commands, which is necessary to prepare the training corpuses for various speaking styles. By introducing constraints on phrase command locations, a better extraction was realized, led to a better performance of the method. Speech synthesis was conducted using HMM speech synthesizer for calm speech and three types of emotional speech. The perceptual experiment showed the designated emotions could be well conveyed with the F0 contours generated by the developed method.
The structure of Escherichia coli BtuF and binding to its cognate ATP binding cassette transporter

Bacterial binding protein-dependent ATP binding cassette (ABC) transporters facilitate uptake of essential nutrients. The crystal structure of Escherichia coli BtuF, the protein that binds vitamin B12 and delivers it to the periplasmic surface of the ABC transporter BtuCD, reveals a bi-lobed fold resembling that of the ferrichrome binding protein FhuD. B12 is bound in the “base-on” conformation in a deep cleft formed at the interface between the two lobes of BtuF. A stable complex between BtuF and BtuCD (with the stoichiometry BtuC2D2F) is demonstrated to form in vitro and was modeled using the individual crystal structures. Two surface glutamates from BtuF may interact with arginine residues on the periplasmic surface of the BtuCD transporter. These glutamate and arginine residues are conserved among binding proteins and ABC transporters mediating iron and B12 uptake, suggesting that they may have a role in docking and the transmission of conformational changes.
Effect of Participation in School Sports Teams on Middle School Students’ Engagement in School

The aim of this study is to determine the effect of participation in school sports teams of students studying in middle school on their levels of school engagement. The relational screening model was used in the study. The study group of the research consisted of a total of 610 students selected by the random sampling method and studying at middle school level (fifth, sixth, seventh, and eighth grades). For analysis of the data obtained from the participants by means of the ‘School Engagement Scale’, descriptive statistics were calculated and interpreted with independent samples t-test and one-way analysis of variance (ANOVA). Based on the research findings, the mean level of school engagement of the participants was found to be 3.62 ± 0.51. In terms of the gender variable, a significant difference in favour of female participants was found. With respect to another variable, that of state of participation in school teams, it was determined that as length of participation in school teams increased, mean level of school engagement of the participants also increased. In conclusion, it was determined that participation in school teams made a positive contribution to students’ engagement in school, and it is recommended that in order to further increase students’ level of school engagement, measures should be taken to ensure students’ participation in school teams.
Hybrid reasoning on OWL RL

Both materialization and backward-chaining as different modes of performing inference have complementary advan- tages and disadvantages. Materialization enables very efficient responses at query time, but at the cost of an expensive up front closure computation, which needs to be redone every time the knowledge base changes. Backward-chaining does not need such an expensive and change-sensitive pre-computation, and is therefore suitable for more frequently changing knowledge bases, but has to perform more computation at query time. Materialization has been studied extensively in the recent semantic web literature, and is now available in industrial-strength systems. In this work, we focus instead on backward-chaining, and we present a general hybrid algorithm to perform efficient backward-chaining reasoning on very large RDF data sets. To this end, we analyze the correctness of our algorithm by proving its completeness using the theory developed in deductive databases and we introduce a number of techniques that exploit the characteristics of our method to execute efficiently (most of) the OWL RL rules. These techniques reduce the computation and hence improve the response time by reducing the size of the generated proof tree and the number of duplicates produced in the derivation. We have implemented these techniques in an experimental prototype called QueryPIE and present an evaluation on both realistic and artificial data sets of a size that is between five and ten billion of triples. The evaluation was performed using one machine with commodity hardware and it shows that (i) with our approach the initial pre-computation takes only a few minutes against the hours (or even days) necessary for a full materialization and that (ii) the remaining overhead introduced by reasoning still allows atomic queries to be processed with an interactive response time. To the best of our knowledge our method is the first that demonstrates complex rule-based reasoning at query time over an input of several billion triples and it takes a step forward towards truly large-scale reasoning by showing that complex and large-scale OWL inference can be performed without an expensive distributed hardware architecture.
Single-Microphone Speech Enhancement Inspired by Auditory System

Title of dissertation: Single-Microphone Speech Enhancement Inspired by Auditory System Majid Mirbagheri, Doctor of Philosophy, 2014 Dissertation directed by: Professor Shihab Shamma, Department of Electrical and Computer Enhancing quality of speech in noisy environments has been an active area of research due to the abundance of applications dealing with human voice and dependence of their performance on this quality. While original approaches in the field were mostly addressing this problem in a pure statistical framework in which the goal was to estimate speech from its sum with other independent processes (noise), during last decade, the attention of the scientific community has turned to the functionality of human auditory system. A lot of effort has been put to bridge the gap between the performance of speech processing algorithms and that of average human by borrowing the models suggested for the sound processing in the auditory system. In this thesis, we will introduce algorithms for speech enhancement inspired by two of these models i.e. the cortical representation of sounds and the hypothesized role of temporal coherence in the auditory scene analysis. After an introduction to the auditory system and the speech enhancement framework we will first show how traditional speech enhancement technics such as wiener-filtering can benefit on the feature extraction level from discriminatory capabilities of spectro-temporal representation of sounds in the cortex i.e. the cortical model. We will next focus on the feature processing as opposed to the extraction stage in the speech enhancement systems by taking advantage of models hypothesized for human attention for sound segregation. We demonstrate a mask-based enhancement method in which the temporal coherence of features is used as a criterion to elicit information about their sources and more specifically to form the masks needed to suppress the noise. Lastly, we explore how the two blocks for feature extraction and manipulation can be merged into one in a manner consistent with our knowledge about auditory system. We will do this through the use of regularized non-negative matrix factorization to optimize the feature extraction and simultaneously account for temporal dynamics to separate noise from speech. SINGLE-MICROPHONE SPEECH ENHANCEMENT INSPIRED BY AUDITORY SYSTEM
KDD-Cup 2004: protein homology task

In this paper we describe the winning model for the performance measure "lowest ranked homologous sequence" (RKL). This was a subtask of the Protein Homology Prediction task of the KDD Cup 2004. The goal was to predict protein homology for different performance metrics. The given data was organized in blocks, each of which corresponds to a specific native sequence. The two metrics average precision (APR) and RKL explicitly make use of this block structure. Our solution consists of two parts. The first one is a global classification SVM not aware of the block structure. The second part is a k-NearestNeighbor scheme for block similarity, used to train ranking SVMs on the fly. Furthermore, we sketch our approach to optimize the root-mean-squared-error and report some alternative solutions that turned out to be suboptimal.
The Rise and Fall of BritainsDNA: A Tale of Misleading Claims, Media Manipulation and Threats to Academic Freedom

Direct-to-consumer genetic ancestry testing is a new and growing industry that has gained widespread media coverage and public interest. Its scientific base is in the fields of population and evolutionary genetics and it has benefitted considerably from recent advances in rapid and cost-effective DNA typing technologies. There is a considerable body of scientific literature on the use of genetic data to make inferences about human population history, although publications on inferring the ancestry of specific individuals are rarer. Population geneticists have questioned the scientific validity of some population history inference approaches, particularly those of a more interpretative nature. These controversies have spilled over into commercial genetic ancestry testing, with some companies making sensational claims about their products. One such company—BritainsDNA—made a number of dubious claims both directly to its customers and in the media. Here we outline our scientific concerns, document the exchanges between us, BritainsDNA and the BBC, and discuss the issues raised about media promotion of commercial enterprises, academic freedom of expression, science and pseudoscience and the genetic ancestry testing industry. We provide a detailed account of this case as a resource for historians and sociologists of science, and to shape public understanding, media reporting and scientific scrutiny of the commercial use of population and evolutionary genetics.
Student classification for academic performance prediction using neuro fuzzy in a conventional classroom

Conventional classroom is still the main learning method applied in undergraduate program of Electrical Engineering and Information Technology Department, Gadjah Mada University. There are several problems in this method, such as large amount of students and limited number of meetings making difficult to understand each student. Student classification is a way to solve the problem by mapping the condition of each student based on certain parameters. Many methods have been applied to classify students that are based on IF-THEN rules and pattern recognition. However, many studies were done on intelligent tutoring systems and e-learning systems, not in a conventional classroom. Moreover, there are no researches that measure basic values by considering intelligence and non-intelligence performances. In this work, a student classification model was developed by applying neuro fuzzy concept; a combination of fuzzy's IF-THEN rules and neural network's ability to learn, so this method has the ability to learn from the generated rules to produce the best classification model. The model can be used to predict students' academic performance. Data were processed using ANFIS Editor-Matlab Fuzzy Logic. The results showed that combination of three parameter values -interest, talent, and motivation- is the best model for students classification, which has training RMSE value 0.12301 and testing average RMSE value 0.25611.
The Effect of Quantum and Charged Particles on the Performance of the Dynamic Vector-evaluated Particle Swarm Optimisation Algorithm

Many problems in the real-world have more than one objective, with at least two objectives in conflict with one another. In addition, at least one objective changes over time. These kinds of problems are called dynamic multi-objective optimisation problems (DMOOPs). Studies have shown that both the quantum particle swarm optimisation (QPSO) and charged particle swarm optimisation (CPSO) algorithms perform well in dynamic environments, since they maintain swarm diversity. Therefore, this paper investigates the effect of using either QPSOs or CPSOs in the sub-swarms of the dynamic vector-evaluated particle swarm optimisation (DVEPSO) algorithm. These DVEPSO variations are then compared against the default DVEPSO algorithm that uses gbest PSOs and DVEPSO using heterogeneous PSOs that contain both charged and quantum particles. Furthermore, all of the aforementioned DVEPSO configurations are compared against the dynamic multi-objective optimisation (DMOPSO) algorithm that was the winning algorithm of a comprehensive comparative study of dynamic multi-objective optimisation algorithms. The results indicate that charged and quantum particles improve the performance of DVEPSO, especially for DMOOPs with a deceptive POF and DMOOPs with a non-linear POS.
A Hybrid Approach to Modulation Recognition for Intentional Modulation on Pulse (IMOP) Applications

In this paper, a hybrid approach to modulation recognition is proposed for classifying unmodulated CW, narrow-band FM, wide-band FM, triangular FM, BPSK, DSB-SC and AM as well as noise. The algorithm is based on the use of decision theoretic and pattern recognition techniques. The decision theoretic approach is used to separate noise from signals, constant-envelope from varying-envelope waveforms, unmodulated CW from waveforms with phase information, and the two varying-envelope waveforms from one another. The pattern recognition technique is used to distinguish the three FM and BPSK waveforms. Computer simulations are used to demonstrate the performance of the proposed algorithm