Miracle-dz/UniFAR-FTUs huggingface dataset:
Genetic Tools for Studying Adaptation and the Evolution of Behavior

The rapid expansion of genomic and molecular genetic techniques in model organisms, and the application of these techniques to organisms that are less well studied genetically, make it possible to understand the genetic control of many behavioral phenotypes. However, many behavioral ecologists are uncertain about the value of including a genetic component in their studies. In this article, we review how genetic analyses of behavior are central to topics ranging from understanding past selection and predicting future evolution to explaining the neural and hormonal control of behavior. Furthermore, we review both new and old techniques for studying evolutionary behavior genetics and highlight how the choice of approach depends on both the question and the organism. Topics discussed include genetic architecture, detecting the past history of selection, and genotype‐by‐environment interactions. We show how these questions are being addressed with techniques including statistical genetics, QTL analyses, transgenic analyses, and microarrays. Many of the techniques were first applied to the behavior of genetic model organisms such as laboratory mice and flies. Two recent developments serve to expand the relevance of such studies to behavioral ecology. The first is to use model organisms for studies of the genetic basis of evolutionarily relevant behavior and the second is to apply methods developed in model genetic systems to species that have not previously been examined genetically. These conceptual advances, along with the rapid diversification of genetic tools and the recognition of widespread genetic homology, suggest a bright outlook for evolutionary genetic studies. This review provides access to tools through references to the recent literature and shows the great promise for evolutionary behavioral genetics.
The feasibility of automated online flow cytometry for in-situ monitoring of microbial dynamics in aquatic ecosystems

Fluorescent staining coupled with flow cytometry (FCM) is often used for the monitoring, quantification and characterization of bacteria in engineered and environmental aquatic ecosystems including seawater, freshwater, drinking water, wastewater, and industrial bioreactors. However, infrequent grab sampling hampers accurate characterization and subsequent understanding of microbial dynamics in all of these ecosystems. A logic technological progression is high throughput and full automation of the sampling, staining, measurement, and data analysis steps. Here we assess the feasibility and applicability of automated FCM by means of actual data sets produced with prototype instrumentation. As proof-of-concept we demonstrate examples of microbial dynamics in (i) flowing tap water from a municipal drinking water supply network and (ii) river water from a small creek subject to two rainfall events. In both cases, automated measurements were done at 15-min intervals during 12–14 consecutive days, yielding more than 1000 individual data points for each ecosystem. The extensive data sets derived from the automated measurements allowed for the establishment of baseline data for each ecosystem, as well as for the recognition of daily variations and specific events that would most likely be missed (or miss-characterized) by infrequent sampling. In addition, the online FCM data from the river water was combined and correlated with online measurements of abiotic parameters, showing considerable potential for a better understanding of cause-and-effect relationships in aquatic ecosystems. Although several challenges remain, the successful operation of an automated online FCM system and the basic interpretation of the resulting data sets represent a breakthrough toward the eventual establishment of fully automated online microbiological monitoring technologies.
Linearity of the function between the sound pressure level of speech and the negative peak amplitude of the differentiated glottal flow for voices of different intensities

The negative peak amplitude of the differentiated glottal flow (dpeak) is known to correlate strongly with the sound pressure level (SPL) of speech. Therefore, the function between dpeak and SPL is usually modeled as a single line. In this survey, the relationship between dpeak and SPL is revisited by analyzing glottal flows inverse filtered from speech so unds of largely different intensities. It is shown that in modeling SPL-dpeakgraphs the slope of the line matching soft phonation is larger than the slope of the line for normal and loud speech. This result suggests that vocal intensity is affected not only by the single amplitude domain value of the voice source, dpeak, but also by the shape of the differentiated glottal flow near the instant of the
Survey on Web Wining Technologies

Web mining techniques should have the analysis of information originated in the web must be helpful to all users for what they are looking for the personalization of site according to users understanding in website should adopt web data accurately. Only simple context like free text only cannot be so much attracted by all the users. Web site structure have to play major role with special techniques , significant patterns about the preferences and user behaviour to personalize the web site. Many times web site structure seems to be complex , hiding the data which causes “ Lost in Hyperspace”. In this paper let we go through main web mining techniques for the accurate targeted knowledge on the user behaviour in site. It is the combination of hybrid and intelligence techniques for web data mining.
Automatic Evolution of Multimodal Behavior with Multi-Brain HyperNEAT

An important challenge in neuroevolution is to evolve multimodal behavior. Indirect network encodings can potentially answer this challenge. Yet in practice, indirect encodings do not yield effective multimodal controllers. This paper introduces novel multimodal extensions to HyperNEAT, a popular indirect encoding. A previous multimodal approach called situational policy geometry assumes that multiple brains benefit from being embedded within an explicit geometric space. However, this paper introduces HyperNEAT extensions for evolving many brains without assuming geometric relationships between them. The resulting Multi-Brain HyperNEAT can exploit human-specified task divisions, or can automatically discover when brains should be used, and how many to use. Experiments show that multi-brain approaches are more effective than HyperNEAT without multimodal extensions, and that brains without a geometric relation to each other are superior.
Upper Limb Evaluation and One-Year Follow Up of Non-Ambulant Patients with Spinal Muscular Atrophy: An Observational Multicenter Trial

Assessment of the upper limb strength in non-ambulant neuromuscular patients remains challenging. Although potential outcome measures have been reported, longitudinal data demonstrating sensitivity to clinical evolution in spinal muscular atrophy patients are critically lacking. Our study recruited 23 non-ambulant patients, 16 patients (males/females = 6/10; median age 15.4 years with a range from 10.7 to 31.1 years) with spinal muscular atrophy type II and 7 patients (males/females = 2/5; median age 19.9 years with a range from 8.3 to 29.9 years) with type III. The Brooke functional score was on median 3 with a range from 2 to 6. The average total vital capacity was 46%, and seven patients required non-invasive ventilation at night. Patients were assessed at baseline, 6 months, and 1 year using the Motor Function Measure and innovative devices MyoGrip, MyoPinch, and MoviPlate, which assess handgrip strength, key pinch strength, and hand/finger extension-flexion function, respectively. The study demonstrated the feasibility and reliability of these measures for all patients, and sensitivity to negative changes after the age of 14 years. The younger patients showed an increase of the distal force in the follow-up period. The distal force measurements and function were correlated to different functional scales. These data represent an important step in the process of validating these devices as potential outcome measures for future clinical trials. Trial Registration ClinicalTrials.gov NCT00993161
Thermal Image Analysis for Polygraph Testing Two-Dimensional Physiological Measurements Can Serve As an Additional Scoring Channel for Increased Accuracy

Polygraph testing is a standard security procedure favored by the U.S. government. The objective of polygraph testing is to ascertain if the subject under investigation truthfully or deceitfully answers the questions at hand. Specially trained psychologists structure the questions to maximize elicitation. During the testing three physiological parameters are monitored closely: a) blood volume and pulse changes b) respiratory changes c) electrodermal activity. They are all recorded using invasive methods and produce scalar values over time (signals). Then, a scoring system is used to quantify the subject’s response and classify it as deceitful or truthful. An extensive account of state-of-the-art polygraph methods and systems can be found in [3]. The success rate for polygraph testing varies, but on average it is in the neighborhood of 90%. The U.S. government is interested in increasing this rate through the use of additional information channels [4]. One very promising channel is the use of infrared facial image analysis. There are several advantages to this method. 1) It is noninvasive. This is very important in the context of polygraph testing where it is crucial for the subject to feel as comfortable as possible. 2) After appropriate processing the thermal imagery can yield physiological information similar to one of the traditional polygraph channels; i.e., blood flow rate. The major difference is that this in-
Disease Severity and Mortality Can Be Independently Regulated in a Mouse Model of Experimental Graft versus Host Disease

Graft versus host disease (GVHD) is the major limitation of allogeneic hematopoietic stem cell transplantation (HSCT) presenting high mortality and morbidity rates. However, the exact cause of death is not completely understood and does not correlate with specific clinical and histological parameters of disease. Here we show, by using a semi-allogeneic mouse model of GVHD, that mortality and morbidity can be experimentally separated. We injected bone marrow-derived dendritic cells (BMDC) from NOD2/CARD15-deficient donors into semi-allogeneic irradiated chimaeras and observed that recipients were protected from death. However, no protection was observed regarding clinical or pathological scores up to 20 days after transplantation. Protection from death was associated with decreased bacterial translocation, faster hematologic recovery and epithelial integrity maintenance despite mononuclear infiltration at day 20 post-GVHD induction with no skew towards different T helper phenotypes. The protected mice recovered from aGVHD and progressively reached scores compatible with healthy animals. Altogether, our data indicate that severity and mortality can be separate events providing a model to study transplant-related mortality.
A Mininet-based Virtual Testbed for Distributed SDN Development

The need for fault tolerance and scalability is leading to the development of distributed SDN operating systems and applications. But how can you develop such systems and applications reliably without access to an expensive testbed? We continue to observe SDN development practices using full system virtualization or heavyweight containers, increasing complexity and overhead while decreasing usability. We demonstrate a simpler and more efficient approach: using Mininet's cluster mode to easily deploy a virtual testbed of lightweight containers on a single machine, an ad hoc cluster, or a dedicated hardware testbed. By adding an open source, distributed network operating system such as ONOS, we can create a flexible and scalable open source development platform for distributed SDN system and application software development.
Forward search with discontinuous probabilities for online handwriting recognition

Tree structured time-synchronous search methods have proven to be very effective in speech recognition systems, providing a framework in which information about words and language structure can be easily added. It is desirable to apply these same methods to handwriting. However, to apply these search methods it is necessary that every hypothesis can be scored at every point in time, and these scores must accumulate monotonically as the search proceeds. Many of the most efficient character recognizers in online handwriting recognition systems do not provide scores that meet these constraints. If these constraints aren't met, the search algorithm can no longer prune theories based on their scores lending to an impractical search space size. This paper describes a novel method and protocol that allows discontinuous probability scores of the type produced by many character recognizers to be used with tree structured search methods such as beam and Viterbi search.
Short-Term Load Forecasting Based on the Method of Genetic Programming

The algorithm of genetic programming is described and applied to short-term load forecasting. For the fault in history load data, the load samples are filtered and processed generally before using, and then the load series of the same time point but different days are chosen as the training sets. According to the complex expressive capacity of genetic programming, the future short-term load model of different time point is forecasted by time-sharing. This method of genetic programming can find out relevant elements to electric load data automatically, so the artificial errors in forecasting can be avoided effectively. And the future load value of each time point can be calculated with the corresponding model created. Finally, it proves that the method of genetic programming in short-term load forecasting is better through out comparison between the results forecasted by genetic programming and time series.
The diffuse multipath component and multipath component visibility

This work studies the effect of spatial variation of the multipath structure on the diffuse multipath component (DMC). The DMC is quantified in simulated and measured channels, using two versions of SAGE. Using a ‘classic’ implementation of SAGE, the DMC increases as the visibility regions of multipath components decrease in size. An implementation of SAGE that takes into account visibility regions of multipath components achieves lower DMC over both simulated and measured channels.
Co-tutorat et médiation instrumentale : une formule propice à l'apprentissage pour les élèves non francophones

Notre contribution presente une experience menee dans une Classe d'Accueil pour eleves Non Scolarises Anterieurement (CLANSA), dans un college de Cayenne. Notre etude presentant un caractere exploratoire, se propose d'analyser l'impact d'une activite experimentale concue a cet effet, a la fois sur (1) la socialisation des eleves et sur (2) l'acquisition des competences en francais - tant en expression orale qu'ecrite -, ainsi que sur (3) l'acquisition de savoirs techniques concernant l'utilisation d'un environnement informatique. L'originalite de l'experience reside dans le caractere meme de l'activite (un debat argumente medie par ordinateur en situation de tutorat interclasses) et dans la constitution des groupes de discussion. Chacun des groupes est forme de deux binomes d'eleves, les deux partenaires de chaque binome ayant des competences complementaires : l'eleve de 6eme maitrisant la langue francaise - expression orale et ecrite - et l'eleve de la classe d'accueil maitrisant le logiciel pour l'avoir utilise lors d'une precedente activite (voir ci-apres). Les deux groupes classe 6eme/ CLANSA manifestent un interet egal pour le sujet du debat : " les jeux videos, pour ou contre ".
A Stealth Intervention: The GLAMA (Girls! Lead! Achieve! Mentor! Activate!) and BLAST (Boys! Lead! Activate! Succeed Together!) School Connectedness, Peer Leadership and Physical Activity Transition Program

This study investigated the effects of the GLAMA (Girls! Lead! Achieve! Mentor! Activate! ) and BLAST (Boys! Lead! Activate! Succeed Together! ) controlled 8-week peer-led stealth intervention on school connectedness and physical activity self-efficacy(PASE). The GLAMA and BLAST sessions were conducted during curriculum time in an Australian state secondary school by 49 Year 10 student leaders and 206 Year 7 students. Year 7 school connectedness decreased in both the control and intervention schools (p < .001). Baseline social self-efficacy was the largest single predictor of change in Year 7 school connectedness (p < .001). PASE increased in both schools over the 8-weeks (p=.054), with the intervention school improving more. School connectedness may require greater time to elicit positive changes and integrated curriculum approaches that include ongoing peer mentoring are warranted. As school connectedness is a protective factor for many public health outcomes, a stealth approach requires further investigation particularly exploring the role of process motivators.
Validity of Pitch Velocity and Strike Percentage to Assess Fatigue in Young Baseball Pitchers

Although coaches chart pitch velocity (PV) and strike percentage (SP) to assess pitcher fatigue levels, the validity of these tools has not been quantified in young pitchers. The purpose of this study was to compare PV and SP across levels of perceived fatigue in young pitchers. Data describing PV, first strike percentage (SP1st), total strike percentage (SPT) and perceived fatigue (PFL) throughout a simulated performance were recorded for 14 pitchers. Differences within PV, SP1st, and SPT were compared across PFLs utilizing repeated measures analysis of variance. PF was the independent variable and PV, SP1st, and SPT were the dependent variables. Results indicated no differences in PV across fatigue levels. SPT increased significantly from PFL 0 to PFL 1 (p = 0.0250). SP1st also increased significantly between PFL 0 and PFL 1 (p = 0.0040) before decreasing significantly for PFL 2 (p < 0.001). These results indicate that the tracking of PV may not be a valid tool for assessing fatigue. However, tracking both SP1st and SPT may be valid tools for assessing fatigue and may provide coaches with evidence of the onset of fatigue.
Analysis and modeling of GaAs-based coupled microstrip lines

This paper describes one of the critical technologies of very high speed integrated circuits (VHSICs), the equivalent circuit model of the GaAs substrate based coupled microstrip lines. We present a method that extracts a frequency-dependent tabular RLGC model from mixed-mode S-parameters estimated by EM simulation (software HFSS). This paper shows that the using a conventional modal decomposition can extend a two-line method for a single transmission line to a two-line method for a symmetrical coupled pair. This method can be contributed to establish the component library and analyze crosstalk and delays for GaAs-based transmission lines used in VHSICs widely.
Cross-Validation of the Spanish HP-Version of the Jefferson Scale of Empathy Confirmed with Some Cross-Cultural Differences

Context: Medical educators agree that empathy is essential for physicians' professionalism. The Health Professional Version of the Jefferson Scale of Empathy (JSE-HP) was developed in response to a need for a psychometrically sound instrument to measure empathy in the context of patient care. Although extensive support for its validity and reliability is available, the authors recognize the necessity to examine psychometrics of the JSE-HP in different socio-cultural contexts to assure the psychometric soundness of this instrument. The first aim of this study was to confirm its psychometric properties in the cross-cultural context of Spain and Latin American countries. The second aim was to measure the influence of social and cultural factors on the development of medical empathy in health practitioners. Methods: The original English version of the JSE-HP was translated into International Spanish using back-translation procedures. The Spanish version of the JSE-HP was administered to 896 physicians from Spain and 13 Latin American countries. Data were subjected to exploratory factor analysis using principal component analysis (PCA) with oblique rotation (promax) to allow for correlation among the resulting factors, followed by a second analysis, using confirmatory factor analysis (CFA). Two theoretical models, one based on the English JSE-HP and another on the first Spanish student version of the JSE (JSE-S), were tested. Demographic variables were compared using group comparisons. Results: A total of 715 (80%) surveys were returned fully completed. Cronbach's alpha coefficient of the JSE for the entire sample was 0.84. The psychometric properties of the Spanish JSE-HP matched those of the original English JSE-HP. However, the Spanish JSE-S model proved more appropriate than the original English model for the sample in this study. Group comparisons among physicians classified by gender, medical specialties, cultural and cross-cultural backgrounds yielded statistically significant differences (p < 0.001). Conclusions: The findings support the underlying factor structure of the Jefferson Scale of Empathy (JSE). The results reveal the importance of culture in the development of medical empathy. The cross-cultural differences described could open gates for further lines of medical education research.
Impact of human factors on email worm propagation

One of the most prevalent security problems in network is the rampant propagation of email worms. Unlike active worms, the email worm has to be activated by user action in order to spread further. This paper deals with modeling email worm propagation by analyzing and combining human factors. Impact of human factors on email worm propagation is investigated and discussed. Results of email worm propagation under a practical simulation environment show that the presented model well describes the email worm behavior. Conclusions are also drawn that infection probability decreases during evolution of worm infection due to the security consciousness rising, and highly connected nodes are more susceptible.
Efficient text independent speaker identification based on GFCC and CMN methods

The performance of automatic speaker identification systems degrade drastically in the presence of noise and other distortions, especially when there is a noise level mismatch between the training and testing environments. In this experimental research we have studied a recently robust front-end algorithm based on Gammatone Frequency Cepstral Coefficients GFCC combined to Cepstral Mean Normalization CMN technique. Our system using a Gaussian Mixture Models GMM classifier are implemented and tested under MATLAB®7 programming environment with multilevel White Gaussian Noise WGN applied to a test utterances using our proper database containing 51 Arabic speakers. Our aim is to study the performance of this suggested architecture and make a comparison with the conventional Mel Frequency Cepstral Coefficients MFCC method which we have successfully implemented and tested in the previous work. The obtained experimental results confirm the superior performance of the proposed method over MFCC and outperform it in different noisy environments. Our evaluations based on the recognition rate accuracy show that both MFCC and the proposed feature extractor have perfects performances in low-noise environments when Signal per Noise Ratio SNR is greater than 35 dB (practically 100% in all cases), but when the SNR of test signal changed from 0 to 40 dB, the average accuracy of the MFCCs methods is only 50.05%, while the proposed GFCCs extractors combined to CMN normalization still achieves an average accuracy of 55.43%.