Miracle-dz/UniFAR-FTUs huggingface dataset:
Candidate gene–environment interactions and their relationships with timing of breeding in a wild bird population

Monitoring and predicting evolutionary changes underlying current environmental modifications are complex challenges. Recent approaches to achieve these objectives include assessing the genetic variation and effects of candidate genes on traits indicating adaptive potential. In birds, for example, short tandem repeat polymorphism at four candidate genes (CLOCK, NPAS2, ADCYAP1, and CREB1) has been linked to variation in phenological traits such as laying date and timing of migration. However, our understanding of their importance as evolutionary predictors is still limited, mainly because the extent of genotype–environment interactions (GxE) related to these genes has yet to be assessed. Here, we studied a population of Tree swallow (Tachycineta bicolor) over 4 years in southern Québec (Canada) to assess the relationships between those four candidate genes and two phenological traits related to reproduction (laying date and incubation duration) and also determine the importance of GxE in this system. Our results showed that NPAS2 female genotypes were nonrandomly distributed across the study system and formed a longitudinal cline with longer genotypes located to the east. We observed relationships between length polymorphism at all candidate genes and laying date and/or incubation duration, and most of these relationships were affected by environmental variables (breeding density, latitude, or temperature). In particular, the positive relationships detected between laying date and both CLOCK and NPAS2 female genotypes were variable depending on breeding density. Our results suggest that all four candidate genes potentially affect timing of breeding in birds and that GxE are more prevalent and important than previously reported in this context.
Denoising of Fingerprint Images using Q-shift Complex Wavelet Transform

In this paper, we present a novel image denoising method using Q-shift with Dual Tree Complex Wavelet Transform (QDTCWT) for denoising fingerprint images. The DTCWT is an over complete wavelet transform with limited redundancy and generates complex coefficients in parallel using a dual tree of wavelet filters. But, low pass delay produces a Hilbert pair relationship between two trees. This is well addressed by Q-shift filters for improving orthogonality and symmetry properties in level 2 and below. QDTCWT have features like linear phase, tight frame, compact spatial support, good frequency domain selectivity with low sidelobe levels, approximate shift invariance, and good directional selectivity in two or more dimensions. This provides the QDTCWT basis mainly useful for de-noising purposes with high degree of shift-invariance and better directionality compared to the other traditional methods. The proposed algorithm has been designed in the MATLAB TM environment and tested in the fingerprint images obtained from the FVC2004 database for denoising. The performance and efficiency of the algorithm are estimated by calculating various quality metrics and compared with the advanced methods already practiced in fingerprint image denoising. The results of this study revealed that the QDTCWT algorithm is capable of producing high quality finger print images with greater fidelity, high robustness and accuracy over the other traditional denoising methods.
Heart rate variability as an indicator of autonomous nervous system activity in children with attention deficit hyperactivity disorder

Objective: The aim of the present study was to evaluate heart rate variability (HRV) in children newly diagnosed as attention-deficit/hyperactivity disorder (ADHD). Methods: A total of 51 children with new ADHD diagnosis who were not received any treatment formed the study group and 51 age and sex-matched healthy children were en-rolled as the control group. 24-hour heart rate (HR) recordings were performed with rhythm Holter monitoring and HRV parameters indicating autonomous nervous system (ANS) functions were evaluated. Children in ADHD group were further divided into two groups as severe and mild ADHD according to Clinical Global Impressions-ADHD-Severity scale. Results: HRV parameters were comparable between ADHD and control groups. Whereas, percent-age of consecutive NN intervals over 50 msn (pNN50) and minimum Spectral Power per hour (minSPH) values were lower; while, maximum 1-hour heart rate Holter (maxHRH) and mean heart rate (HR) values were higher in severe ADHD group than those of control group. Conclusion: These results support that as the severity of ADHD increases, ANS dysfunction becomes more overt. Further large scale, multi-centered, randomized-controlled clinical trials are needed to clarify possible role of ANS dysfunction in ADHD etiopathogenesis.
Beyond Deep Learning: Scalable Methods and Models for Learning

In my thesis I explored several techniques to improve how to efficiently model signal representations and learn useful information from them. The building block of my dissertation is based on machine learning approaches to classification, where a (typically non-linear) function is learned from labeled examples to map from signals to some useful information (e.g. an object class present an image, or a word present in an acoustic signal). One of the motivating factors of my work has been advances in neural networks in deep architectures (which has led to the terminology ``deep learning''), and that has shown state-of-the-art performance in acoustic modeling and object recognition -- the main focus of this thesis. In my work, I have contributed to both the learning (or training) of such architectures through faster and robust optimization techniques, and also to the simplification of the deep architecture model to an approach that is simple to optimize. Furthermore, I derived a theoretical bound showing a fundamental limitation of shallow architectures based on sparse coding (which can be seen as a one hidden layer neural network), thus justifying the need for deeper architectures, while also empirically verifying these architectural choices on speech recognition. Many of my contributions have been used in a wide variety of applications, products and datasets as a result of many collaborations within ICSI and Berkeley, but also at Microsoft Research and Google Research.
40-Gbps vestigial sideband half-cycle Nyquist subcarrier modulation transmission experiment and its comparison with orthogonal frequency division multiplexing

Abstract. We experimentally demonstrate the superior performance of a 40-Gbps 16-QAM half-cycle Nyquist subcarrier modulation (SCM) transmission over a 100-km uncompensated standard single-mode fiber using dual-drive Mach-Zehnder modulator-based vestigial sideband intensity modulation and direct detection. The impact of modulator chirp on the system performance is experimentally evaluated. This Nyquist-SCM technique is compared with optical orthogonal frequency division multiplexing in both back-to-back and 100-km transmission experiments, and the results show that the Nyquist system has a better performance.
Mining User Interests from Personal Photos

Personal photos are enjoying explosive growth with the popularity of photo-taking devices and social media. The vast amount of online photos largely exhibit users' interests, emotion and opinions. Mining user interests from personal photos can boost a number of utilities, such as advertising, interest based community detection and photo recommendation. In this paper, we study the problem of user interests mining from personal photos. We propose a User Image Latent Space Model to jointly model user interests and image contents. User interests are modeled as latent factors and each user is assumed to have a distribution over them. By inferring the latent factors and users' distributions, we can discover what the users are interested in. We model image contents with a four-level hierarchical structure where the layers correspond to themes, semantic regions, visual words and pixels respectively. Users' latent interests are embedded in the theme layer. Given image contents, users' interests can be discovered by doing posterior inference. We use variational inference to approximate the posteriors of latent variables and learn model parameters. Experiments on 180K Flickr photos demonstrate the effectiveness of our model.
Elimination of Transients in Time-Varying Allpass Fractional Delay Filteres with Applications to Digital Waveguide Modeling

This paper considers discrete-time allpass filters that implement a time-varying fractional delay. These recursive filters are desirable from the point of view of implementational efficiency and flat magnitude response, but they are prone to transient effects when their parameters are changed. A state variable update approach to this problem is reviewed, the basic idea of which is to modify also the state of the filter when coefficients are changed so that the filter enters a new state smoothly without transient attacks. This method is adapted to give a new and simple practical method for eliminating the transients. The effectiveness of the new technique is verified by applying it to a digital waveguide model of a vibrating string.
Modeling verbal inflection for English to German SMT

German verbal inﬂection is frequently wrong in standard statistical machine translation approaches. German verbs agree with subjects in person and number, and they bear information about mood and tense. For subject–verb agreement, we parse German MT output to identify subject–verb pairs and ensure that the verb agrees with the subject. We show that this approach improves subject-verb agreement. We model tense/mood translation from English to German by means of a statistical classiﬁcation model. Although our model shows good results on well-formed data, it does not systematically improve tense and mood in MT output. Reasons include the need for discourse knowledge, dependency on the domain, and stylistic variety in how tense/mood is translated. We present a thorough analysis of these problems.
Automatic estimation of DVFS potential

Engineers obsessed in the past with augmenting application performance. Nowadays, as the energy price tag and ecological concerns rise, administrators and engineers are considering the energy consumption metric as new optimization criteria. In order to decrease energy consumption, one known solution is Dynamic Voltage Frequency Scaling (DVFS). DVFS allows users to modify the CPU frequency in order to reduce energy consumption. Although the technique is efficient, its real potential is often difficult to predict. The following paper presents UtoPeak, a tool able to compute the sequence of frequencies providing the lowest energy consumption for a given program execution. Associated to the ideal frequency sequence, Utopeak predicts, ahead of time, the potential impact of DVFS on energy consumption. The paper shows how Utopeak is able to predict the potential gains for known benchmark suites. Utopeak's accuracy in predicting the best energy consumption is 95.6% in average on the benchmark suites SPEC2006 and NAS.
Interpreting the clustering of radio sources

We develop the formalism required to interpret, within a CDM framework, the angular clustering of sources in a deep radio survey. The effect of non-linear evolution of density perturbations is discussed, as is the effect of the assumed redshift distribution of sources. We also investigate what redshift ranges contribute to the clustering signal at different angular scales. Application of the formalism is focused on the clustering detected in the FIRST survey, but measurements made for other radio surveys are also investigated. We comment on the implications for the evolution of clustering.
Simulation the functionality of a laser pulse image acquisition system

The goal of this paper is to generate a laser pulse and to capture it by an image acquisition system. We use a confocal resonator to generate a laser pulse; then the generate light is focused in to an optical fiber using a lens; the light propagates through the fiber and at the fiber output light is projected on a CMOS sensor. We compute the PSF (point spread function) and MTF (modulation transfer function) in order to characterize the functionality of the lens and the optical part of a CMOS sensor. We analyze the CMOS electrical part considering the photon shot noise and the FPN (fixed pattern noise). Finally, we use a Lapacian filter, an amplitude filter and a bilateral filter in order to reconstruct the noisy blurred image. We consider the image capture system to be linear shift invariant, axial and the light is orthogonal to the system.
CONSTRUCCIÓN DEL REGISTRO DE OBSERVACIÓN PARA EL ANÁLISIS DEL MOVIMIENTO FUNDAMENTADO EN LA TEORÍA DE LABAN

En este articulo se describe el proceso de construccion de un Registro de Observacion inspirado en el Analisis del Movimiento de Laban (ROAM) en personas con Discapacidad Intelectual (DI). La aplicacion del ROAM permite obtener una medida objetiva y estandarizada sobre las tendencias generales de movimiento de la persona, ademas de poder utilizarse en observaciones pre y post intervenciones y asi conocer los cambios de movimiento del individuo. El del ROAM se desarrollo en varias fases, en la primera de las cuales se identificaron los elementos basicos para el registro y se realizaron diversas versiones del ROAM mediante la tecnica de jueces expertos. En las fases posteriores se realizo el estudio exploratorio, utilizando el registro para evaluar dos sesiones de danza movimiento terapia en un grupo de adultos con DI. Los resultados muestran que el ROAM presenta unos buenos indices de validez de contenido y de fiabilidad inter e intra observadores (0.72), por tanto, el ROAM permitio analizar las caracteristicas generales del movimiento de las personas con DI que participaron en el estudio exploratorio.
History and asymmetric sierpinski carpet based employment recommendation

In recent years, with more and more college students graduating, the employment becomes a serious problem, which attracts more and more attention. Therefore, it is imperative to develop the platform for employment recommendation. The existing employment recommendation systems only take into account several properties such as salary, employment description and the major of the applicant. However, they ignored the history information and didn't analyze the students that have been employed previously. To address this problem, this paper proposed a history and asymmetric sierpinski carpet based employment recommendation system. This system first analyzes the similarity between companies according to the history of their staff information. Then the asymmetric sierpinski carpet is used as a layout algorithm to visualize the recommendations. In addition, several interaction techniques are developed to adjust the visualization process. Finally, this paper implements an experiment to argue that our work is feasible and effective.
Multimodal Interactive Advertising

An implementation of a multimodal interactive advertising system is described in this paper. The system integrates computer vision and speech recognition technologies to allow the advertising display to determine when a customer is nearby and to respond to that customer’s location in space, gestures and speech. The advertising application is described here in detail. The system architecture and hardware/software modules involved are presented in overview. The application has been tested in the laboratory and exhibition hall settings but has not yet been deployed in public.
Change in Medication Adherence and Beliefs in Medicines Over Time in Older Adults

Objective: The temporal component of medication adherence is important while designing interventions to improve medication adherence. Thus, the objective of this study was to determine how medication adherence and beliefs in medicines change over time in older adults. Methods: A two-year longitudinal internet-based survey among adults 65+ years was used to collect data on medication adherence (Morisky 4-item scale) and beliefs in medicines (Beliefs about Medicines Questionnaire). Paired t-test and one-way ANOVA determined if a change in beliefs in medicines and medication adherence over time was significant. A multiple linear regression was used to determine the significant predictors of change in medication adherence over time. Results: 436 respondents answered both baseline and follow-up surveys. Among all respondents, there was no significant change in adherence (0.58 ± 0.84 vs. 0.59 ± 0.84; p > 0.05), necessity beliefs (17.13 ± 4.31 vs. 17.10 ± 4.29; p > 0.05), or concern beliefs (11.70 ± 3.73 vs. 11.68 ± 3.77; p > 0.05) over time. For older adults with lower baseline adherence, there was a statistically significant improvement in adherence (1.45 ± 0.70 vs. 0.99 ± 0.97; p < 0.05); but no change in beliefs in medicines over time. The significant predictors of change in medication adherence over time were baseline adherence and baseline concern beliefs in medicines. Conclusion: With baseline adherence and baseline concern beliefs in medicines playing a significant role in determining change in adherence behavior over time, especially in individuals with lower adherence, it is important to alleviate medication concerns at the beginning of therapy for better adherence.
Anovulation in the prevention of cytotoxic-induced follicular attrition and ovarian failure.

BACKGROUND Gonadal failure secondary to alkylating agents may be related to ovulatory status. The objective of this investigation was to evaluate whether anovulation protected ovarian follicles during treatment with cyclophosphamide. METHODS Four groups (n = 20 mature female Sprague-Dawley rats per group) were studied: control (group I), 5 mg/kg/day cyclophosphamide only (group II), 5 mg/kg/day cyclophosphamide and the combination of 50 micro g ethinyl estradiol/2 mg norgestrel (group III) and 5 mg/kg/day cyclophosphamide and 2.5 micro g leuprolide acetate daily (group IV). Animals were sacrificed after 4 weeks of treatment. Follicles were classified as medium (300-450 micro m) and large (>450 micro m) per section of ovary. RESULTS Group II developed a significantly greater number of medium and large follicles [15.1 +/- 6.1 and 4.9 +/- 1.9 (mean +/- SD), respectively] compared with group I [7.1 +/- 2.1 and 1.0 +/- 0.7 (mean +/- SD), respectively] (P </= 0.05). Groups III and IV developed a significantly greater number of medium follicles [13.2 +/- 2.5 and 10.8 +/- 2.3 (mean +/- SD), respectively) compared with group I (P < or = 0.05). There was a trend toward a greater number of large follicles in groups III and IV when they were compared with group I. There were no differences in medium follicles in groups II, III and IV. No differences were noted in the number of large follicles between groups III and IV (2.9 +/- 1.2 and 2.3 +/- 1.0, respectively). CONCLUSIONS These results suggest that in the rat model, cyclophosphamide exerts a stimulatory effect on the ovary resulting in the greater development of both medium and large follicles. Anovulation conferred no protection against cyclophosphamide-induced gonadal toxicity. These data suggest that in the rat model, cyclophosphamide may result in ovarian failure by enhancing recruitment of follicles regardless of ovulatory status or hormonal milieu.
A Mixed Methods Examination of Gender Disparity in High Schools Implementing Advancement Via Individual Determination (AVID)

This mixed-methods research study offers insights and explanations into gender imbalance in the college readiness program, Advancement Via Individual Determination (AVID). Over 200 schools that have been implementing AVID for more than 4 years across the United States participated in this study. Three years of archived historical data pertaining to school demographic information and AVID certification information was accessed and analyzed to examine recruitment and retention of male and female students over time, as well as student enrollment in rigorous curriculum. Our research indicated that at the high school level, gender disparity became most apparent in the 11th and 12th grades. Results indicated that schools that struggled to recruit and retain boys continued to enroll AVID students, both boys and girls, into rigorous advanced placement curriculum at comparable rates as schools that did not struggle to recruit and retain boys in the program. This indicates that once in AVID, boys and girls are provided equal access to rigor; however, recruiting and retaining boys in AVID continues to be a challenge for AVID schools. Research participants indicated that academic identity, peer and family support, leadership and mentoring opportunities and male role models influence male participation in AVID.
Opportunistic Scheduling for Hybrid Network Coding and Cooperative Relaying Techniques in Wireless Networks

SUMMARY With the purpose of improving the performance of next generation wireless networks, cooperative relaying (CoR) and network coding (NC) are promising techniques. The number of time slots required for NC in bidirectional transmission is less than that required for CoR, and hence, NC can achieve higher throughput performance than CoR. However, the disadvantage of NC is that asymmetric traffic ratio conditions might cause a significant decrease in the bidirectional throughput. In contrast, CoR is robust to asymmetric traffic ratio conditions. In this paper, in order to improve the throughput of NC even under asymmetric traffic ratio conditions, we propose an opportunistic scheduling scheme for hybrid NC and CoR. In the proposed scheduling scheme, the transmission protocol with best throughput performance can be adaptively selected based on instantaneous channel state information. Computer simulation results reveal that the proposed scheduling scheme not only achieve higher throughput than the conventional scheduling scheme but is also robust against asymmetric traffic ratio conditions. By adjusting the scheduler’s parameter, the proposed scheduling scheme can provide a tradeoff between the throughput and the traffic ratio. Moreover, in certain cases, maximizing the throughput of NC and guaranteeing the offered traffic ratio can be achieved at the same time.
Trust Management in an Ad hoc Network of Cellular Phones used in Emergency Conditions

We study the unique trust management, and more precisely reputation management and revocation of malicious ad hoc nodes used for emergency communications. Unlike in centralized systems, reputation management and revocation in ad hoc networks is non-trivial. This difficulty is due to the fact that the nodes have to collaboratively calculate the reputation value of a particular node and then revoke the node if the reputation value goes below a threshold. A major challenge in this scheme is to prevent a malicious node from discrediting other genuine nodes. The decision to revoke a node has to be communicated to all the nodes of the network. In traditional ad hoc networks the overhead of broadcasting the message throughout the network may be very high. We solve the problem of reputation management and node revocation in ad hoc networks of cell phones by using a threshold cryptography based scheme. Each node of the network would have a set of anonymous referees which would store the reputation information of the node and issue reputation certificates to the node with timestamps. The misbehavior of a particular cell phone is reported to its anonymous referees, who issue certificates which reflect the positive and negative recommendations.