Miracle-dz/UniFAR-FTUs huggingface dataset:
Evidence for Letter-Specific Position Coding Mechanisms

The perceptual matching (same-different judgment) paradigm was used to investigate precision in position coding for strings of letters, digits, and symbols. Reference and target stimuli were 6 characters long and could be identical or differ either by transposing two characters or substituting two characters. The distance separating the two characters was manipulated such that they could either be contiguous, separated by one intervening character, or separated by two intervening characters. Effects of type of character and distance were measured in terms of the difference between the transposition and substitution conditions (transposition cost). Error rates revealed that transposition costs were greater for letters than for digits, which in turn were greater than for symbols. Furthermore, letter stimuli showed a gradual decrease in transposition cost as the distance between the letters increased, whereas the only significant difference for digit and symbol stimuli arose between contiguous and non-contiguous changes, with no effect of distance on the non-contiguous changes. The results are taken as further evidence for letter-specific position coding mechanisms.
Influence of student engagement, moods and completed assignments with differentiated homework on normalized gains and growth in reading literature using iPads

The purpose of this study was to investigate how engagement, mood and number of assignments completed on computerized differentiated homework using an iPad in a one-to-one mobile device environment influence the growth index and normalized gain in reading literature benchmark assessments of students in grades five, six, and seven. Furthermore, this study investigated if gender or special education status influences the growth index or normalized gain in reading literature benchmark assessment scores when using an iPad in a one-to-one mobile device environment on computerized differentiated homework. Data from the Northwest Evaluation Association (NWEA) fall Measures of Academic (MAP) Progress assessment was analyzed for students’ areas of weakness in reading literature. Using assessment results, students were assigned differentiated homework to complete on an iPad, while reporting their level of engagement with the app and present mood. Growth and normalized gains were calculated following the spring administration of the NWEA MAP. Five hundred-twelve suburban public school students, grades five, six, and seven were given iPads containing differentiated homework assignments during the 2012-2013 academic year. A one-way group analysis of variance (ANOVA) showed that there was a statistically significant difference for level of engagement with iPad applications among students in grades five, six, and seven. An independent t-test showed that special education students were significantly more engaged with their differentiated homework than non-classified special education students. An independent t-test showed that students
Who Gets Wall Street’s Attention? How Alliance Announcements and Alliance Density Affect Analyst Coverage

This study integrates research on strategic alliances and security analysts by focusing on the extent to which alliance announcements affect the amount of coverage firms obtain from security analysts. Adopting the perspective that alliance announcements constitute important market signals, I argue that they increase analyst coverage at a decreasing rate, but also that the strength of the relationship between announcements and coverage depends on the density of alliances. The relationship is strongest when alliance density is low because more attractive alliance partners are available, or when alliance density is high because more attractive resources are available in the alliance network. I find support for these arguments in the empirical context of alliance announcements among computer technology firms and discuss their consequences for research on alliance-based market signals.
Cold Disks: Spitzer Spectroscopy of Disks around Young Stars with Large Gaps

We have identified four circumstellar disks with a deficit of dust emission from their inner 15-50 AU. All four stars have F-G spectral type and were uncovered as part of the Spitzer Space Telescope "Cores to Disks" Legacy Program Infrared Spectrograph (IRS) first-look survey of ~100 pre-main-sequence stars. Modeling of the spectral energy distributions indicates a reduction in dust density by factors of 100-1000 from disk radii between ~0.4 and 15-50 AU but with massive gas-rich disks at larger radii. This large contrast between the inner and outer disk has led us to use the term "cold disks" to distinguish these unusual systems. However, hot dust [(0.02-0.2)Mmoon] is still present close to the central star (R ≤ 0.8 AU). We introduce the 30 μm/13 μm flux density ratio as a new diagnostic for identifying cold disks. The mechanisms for dust clearing over such large gaps are discussed. Although rare, cold disks are likely in transition from an optically thick to an optically thin state and so offer excellent laboratories for the study of planet formation.
An Estimation Method of Rotational Direction and Speed for Free-Running AC Machines Without Speed and Voltage Sensor

This paper presents an estimation method of rotational direction and speed for free-running ac machines driven by an inverter without speed and voltage sensor. The method has four estimation modes, and it utilizes only the measured phase current of machines. The performance of the proposed method is verified through the experiments for both permanent-magnet synchronous motor and asynchronous machines.
The Size and Strength Development in Elite Youth Ice Hockey Players

Background: Ice hockey is a fast, physical sport that requires high levels of muscular strength, muscular endurance and agility. Objectives: This study was conducted to create a profile including: anthropometric measurement, muscular strength, muscular endurance, lower body jump height and distance, and agility characteristics for elite youth hockey players. Methods: Pre-season off-ice testing results were retrospectively reviewed from a human performance database. Variables included height, weight, body fat percentage, grip strength, push-ups/bench press, supine rows, the plank test, vertical jump, standing long jump, hip adductor and abductor strength, and the 5-10-5 shuttle, and. One-way ANOVAs (1group x 4 time) and Tukeys post-hoc tests were performed to determine changes in the immediately successive age group (p<0.05). Results: Participants included male Bantam-(age: 13-14) and Midget-(age: 15-17) AAA ice-hockey players (n=260). Age categories were grouped as 13 years old (yo)(n=75), 14 yo (n=70), 15 yo (n=58), and 16-17 yo (n=57). Increases between successive age groups were observed in the following variables: weight (13, 14, 15 and 16-17 yo), height (13 and 14 yo), left and right grip strength (13, 14, 15, and 16-17 yo), bench press (15 and 16-17 yo), left and right hip abduction (14, 15, and 16-17 yo), and vertical and standing long jump (13, 14, and 15 yo). Total time for the 5-10-5 shuttle run test decreased from 13 to 14yo, and 14 to 15 yo. Conclusion: Changes with age in off-ice performance variables of elite amateur hockey players should be recognized, followed, and addressed during player development to maximize the potential for elite performance and reduce the risk of injury. Keywords: Athletic Performance, Training, Physical Fitness
Unsupervised key-phrases extraction from scientific papers using domain and linguistic knowledge

The domain of Digital Libraries presents specific challenges for unsupervised information extraction to support both the automatic classification of documents and the enhancement of userspsila navigation in the digital content. In this paper, we propose a combined use of machine learning techniques (i.e. Support Vector Machines) and Natural Language Processing techniques (i.e. Stanford NLP parser) to tackle the problem of unsupervised key-phrases extraction from scientific papers. The proposed method strongly depends on the robust structural properties of a scientific paper as well as on the lexical knowledge that we are able to mine from its text. For the experimental assessment we have use a subset of ACM papers in the Computer Science domain containing 400 documents. Preliminary evaluation of the approach shows promising result that improves - on the same data-set - on state-of-the-art Bayesian learning system KEA from a minimum 27% to a maximum 77% depending on KEA parameters tuning and specific evaluation set. Our assessment is performed by comparison with key-phrases assigned by human experts in the specific domain and freely available through ACM portal.
Redox-active quinones induces genome-wide DNA methylation changes by an iron-mediated and Tet-dependent mechanism

DNA methylation has been proven to be a critical epigenetic mark important for various cellular processes. Here, we report that redox-active quinones, a ubiquitous class of chemicals found in natural products, cancer therapeutics and environment, stimulate the conversion of 5mC to 5hmC in vivo, and increase 5hmC in 5751 genes in cells. 5hmC increase is associated with significantly altered gene expression of 3414 genes. Interestingly, in quinone-treated cells, labile iron-sensitive protein ferritin light chain showed a significant increase at both mRNA and protein levels indicating a role of iron regulation in stimulating Tet-mediated 5mC oxidation. Consistently, the deprivation of cellular labile iron using specific chelator blocked the 5hmC increase, and a delivery of labile iron increased the 5hmC level. Moreover, both Tet1/Tet2 knockout and dimethyloxalylglycine-induced Tet inhibition diminished the 5hmC increase. These results suggest an iron-regulated Tet-dependent DNA demethylation mechanism mediated by redox-active biomolecules.
Hammamet -tunisia " Evaluation and Optimization of Innovative Production Systems of Goods and Services " Inventory Allocation in Multi-period Multi-echelon Logistics Networks of Modular Products

In this study, inventory planning in logistics networks of modular products is investigated in a multi-period and multi-echelon setting. It is shown that this optimization problem can be converted to another problem which is briefly called modular proportional flow problem. This later problem is a minimum cost network flow problem with side constraints. The whole network consists of several disjoint subnetworks requiring the flows in some given sets of arcs to be proportional. Building efficient solution methods to this problem is important since it can be addressed several times as a subproblem. First, we show that the bases of this problem are good forests, and then design a network simplex algorithm that exploits this special structure. Finally, an illustrative example is supplied to demonstrate the algorithm.
An Evaluation of Particle Filters for Contact-SLAM Problems

The contact-SLAM problem is a broad class of grasping and manipulation problem and it is very important to robotic manipulation tasks, particularly when contacts are likely to be intermittent. Several researchers have developed particle filters for C-SLAM problems that estimate the state of manipulated objects, some geometric properties, and their contacts, but the effects of various designing issues are obfuscated by implementation details and are not discussed thoroughly. In this paper, we study the C-SLAM problem restricted to the contact normal direction to understand fundamental modeling choices through analysis of real and simulated experiments. We compare the results of both rigid body and compliant body model with several sources of noise to give users guidance in implementing particle filters for C-SLAM problems.
Evaluating energy consumption of homogeneous MPSoCs using spare tiles

The yield of homogeneous network-on-chip based multi-processor chips can be improved with the addition of spare tiles. However, the impact of this reliability approach on the chip energy consumption is not documented. For instance, in a homogeneous MPSoC, application tasks can be placed onto any tile of a defect-free chip. On the other hand, a chip with defective tile needs a special task placement, where the faulty tile is avoided. This paper presents a task placement tool and the evaluation of energy consumption of homogeneous NoC-based MPSoCs with spare tiles. Results show NoC energy consumption overhead ranging from 1 to 10% when considering up to three faults randomly distributed over the tiles of a 3×4 mesh network. The results also indicate that faults on the central tiles typically have more impact on energy overhead.
Railway track structural health monitoring system

Railway is one of the most used means of transportation. For the railway system to operate flawlessly constant monitoring and inspection of railway tracks is required. Currently railway track inspection and monitoring is done manually which is time taking and not accurate, due to the high chance of human error occurrence. Moreover, practically it is impossible to inspect and monitor the railway track manually as they run thousands of miles. To avoid this we propose a prototype system, designed for continuous monitoring of railway tracks using a combination of sensors. These sensors collect data and through computational analysis faults in the railway tracks are identified. The collected data can help in finding cracks in the tracks and catastrophic accidents can be avoided.
Guided Inquiry Facilitated Blended Learning to Improve Metacognitive and Learning Outcome of High School Students

The learning activities that involve the students to learn actively is one of the characteristics of a qualified education. The learning strategy that involves students’ active learning is guided inquiry. Learning problems today are growing metacognitive skills and cognitive learning outcomes. It is the research and development of learning module by using 4D models of Thiagarajan. The first phase is Define, which analyses the problems and needs required by the prior preparation of the module. The second phase is Design, which formulates learning design and devices to obtain the initial draft of learning modules. The third stage is Develop, which is developing and writing module, module validation, product testing, revision, and the resulting an end-product results module development. The fourth stage is Disseminate, which is disseminating of the valid products. Modules were validated by education experts, practitioners, subject matter experts, and expert of online media. The results of the validation module indicated that the module was valid and could be used in teaching and learning. In the validation phase of testing methods, we used experiments to know the difference of metacognitive skills and learning outcomes between the control group and experimental group. The experimental design was a one group pretest-posttest design. The results of the data analysis showed that the modules could enhance metacognitive skills and learning outcomes. The advantages of this module is as follows, 1) module is accompanied by a video link on a website that contains practical activities that are appropriate to Curriculum 2013, 2) module is accompanied by a video link on a website that contains about manual laboratory activities that will be used in the classroom face-to-face, so that students are ready when doing laboratory activities, 3) this module can be online through chat to increase students’ understanding. The disadvantages of this module are the material presented in the modules is limited. It is suggested that for the better utilisation of the online activities, students should be present at every meeting of the activities, so as to make all the students participate actively. It is also suggested that school set up facilities to support blended learning.
Evaluation of the Cerebral State Index in Cats under Isoflurane Anaesthesia: Dose-Effect Relationship and Prediction of Clinical Signs

The performance of the cerebral state index (CSI) in reflecting different levels of isoflurane anaesthesia was evaluated in ten cats subjected to four end-tidal isoflurane concentrations (EtIso), each maintained for 15 minutes (0.8%, 1.2%, 1.6%, or 2.0% EtIso). The CSI, hemodynamic data, ocular reflexes, and eye position were recorded for each EtIso concentration. Pharmacodynamic analysis of CSI with EtIso was performed, as well as prediction probability analysis with a clinical scale based on the eye reflexes. The CSI values showed great variability. Between all parameters, burst suppression ratio showed the better fitting with the sigmoidal concentration-effect model (R 2 = 0.93) followed by CSI (R 2 = 0.82) and electromyographic activity (R 2 = 0.79). EtIso was the variable with better prediction of the clinical scale of anaesthesia (prediction probability value of 0.94). Although the CSI values decrease with increasing isoflurane concentrations, the huge variability in CSI values may be a strong limitation for its use in cats and it seems to be no better than EtIso as a predictor of clinical signs.
Instant and incremental transformation of models

This work introduces a framework for the instant and incremental transformation of changes among models. It can be configured to understand where and when changes happen in a given source model and the impact these changes have onto a given target model. It can also be configured to select translation rules as needed to update the target model. Incremental transformation is an alternative to the batch transformation and is significantly more efficient in maintaining the synchronicity among large-scale models.
Automated simulation of robotic dynamic systems using a new fuzzy-fractal-genetic approach

We describe a new method for automated simulation of nonlinear dynamical systems. This method is based on a hybrid fuzzy-fractal-genetic approach to achieve, in an efficient way, automated simulation of a particular dynamical system given its mathematical model. The use of genetic algorithms is to achieve automated parameter selection for the mathematical models. The use of fuzzy logic is to simulate the process of expert behavior identification, by implementing the knowledge of identification by a set of fuzzy rules. We also use the concept of the fractal dimension of a time series to help make this identification more accurate. Experimental results for the case of robotic dynamic systems show the efficiency and accuracy of this new method for the simulation of complex nonlinear dynamical systems.
TOMATO PRODUCTION IN SPAIN WITHOUT METHYL BROMIDE

In the Mediterranean area, tomato soilborne pathogens used to be controlled by methyl bromide, particularly in protected cultivation. To decrease the use of this fumigant, non-chemical and chemical alternatives were developed and implemented in many Mediterranean countries. However, the success of the alternative depends on the degree of its integration in an integrated pest management programme.
Decomposable Forward Error Correction Codes Based on Chinese Remainder Theorem

Several applications benefited from multicast data distribution because a sender can concurrently transmit data to multiple receivers using fewer bandwidth. However, reliability is an important issue in multicast because retransmission is not very efficient in multicast. In recent years, Forward Error Correction (FEC) codes are proposed to facilitate reliable multicast data distribution and are applied to several applications. FEC provides a more efficient way of reliable multicast data distribution because of no retransmission. In this paper, we propose a new FEC codes (F-CR codes), which are extended from Chinese Remainder codes, require smaller transmission redundancy than conventional FEC codes and support two variants for transmission and computation efficiency. In particular, the r-decomposition variant allows the sender to decompose an output symbols encoded into r smaller sub-symbols. This decomposable property which is firstly proposed in this paper is especially suitable for link unstable networks or link heterogeneity networks like wireless sensor networks. The analysis and experiments also demonstrate the feasibility of F-CR codes.
ESO imaging survey: infrared observations of CDF-S and HDF-S

This paper presents infrared data obtained from observations carried out at the ESO 3.5 m New Technology Telescope (NTT) of the Hubble Deep Field South (HDF-S) and the Chandra Deep Field South (CDF-S). These data were taken as part of the ESO Imaging Survey (EIS) program, a public survey conducted by ESO to promote follow-up observations with the VLT. In the HDF-S field the infrared observations cover an area of ∼53 square arcmin, encompassing the HST WFPC2 and STIS fields, in the JHK s passbands. The seeing measured in the final stacked images ranges from 0". 79 to 1". 22 and the median limiting magnitudes (AB system, 2" aperture, 5σ detection limit) are J AB ∼ 23.0, H AB ∼ 22.8 and K AB ∼ 23.0 mag. Less complete data are also avai]able in JK s for the adjacent HST NICMOS field. For CDF-S, the infrared observations cover a total area of ∼100 square arcmin, reaching median limiting magnitudes (as defined above) of J AB ∼ 23.6 and K AB ∼ 22.7 mag. For one CDF-S field H band data are also available. This paper describes the observations and presents the results of new reductions carried out entirely through the un-supervised, high-throughput EIS Data Reduction System and its associated EIS/MVM C++-based image processing library developed, over the past 5 years, by the EIS project and now publicly available. The paper also presents source catalogs extracted from the final co-added images which are used to evaluate the scientific quality of the survey products, and hence the performance of the software. This is done comparing the results obtained in the present work with those obtained by other authors from independent data and/or reductions carried out with different software packages and techniques. The final science-grade catalogs together with the astrometrically and photometrically calibrated co-added images are available at CDS.
The Leishmania major BBSome subunit BBS1 is essential for parasite virulence in the mammalian host

Bardet–Biedl syndrome (BBS) is a human genetic disorder with a spectrum of symptoms caused by primary cilium dysfunction. The disease is caused by mutations in one of at least 17 identified genes, of which seven encode subunits of the BBSome, a protein complex required for specific trafficking events to and from the primary cilium. The molecular mechanisms associated with BBSome function remain to be fully elucidated. Here, we generated null and complemented mutants of the BBSome subunit BBS1 in the protozoan parasite, Leishmania. In the absence of BBS1, extracellular parasites have no apparent defects in growth, flagellum assembly, motility or differentiation in vitro but there is accumulation of vacuole‐like structures close to the flagellar pocket. Infectivity of these parasites for macrophages in vitro is reduced compared with wild‐type controls but the null parasites retain the ability to differentiate to the intracellular amastigote stage. However, infectivity of BBS1 null parasites is severely compromised in a BALB/c mouse footpad model. We hypothesize that the absence of BBS1 in Leishmania leads to defects in specific trafficking events that affect parasite persistence in the host. This is the first report of an association between the BBSome complex and pathogen infectivity.