Miracle-dz/UniFAR-FTUs huggingface dataset:
Prenatal Bisphenol A Exposure and Child Behavior in an Inner-City Cohort

Background: Experimental laboratory evidence suggests that bisphenol A (BPA), an endocrine disruptor, is a neurodevelopmental toxicant. However, there have been limited and inconclusive results with respect to sex-specific BPA effects on child behavior. Objective: We examined the association between prenatal BPA exposure and child behavior, adjusting for postnatal BPA exposure and hypothesizing sex-specific effects. Methods: We followed African-American and Dominican women and their children from pregnancy to child’s age 5 years, collecting spot urine samples from the mothers during pregnancy (34 weeks on average) and from children between 3 and 4 years of age to estimate BPA exposure. We assessed child behavior between 3 and 5 years of age using the Child Behavior Checklist (CBCL) and used generalized linear models to test the association between BPA exposure and child behavior, adjusting for potential confounders. Results: The analysis was conducted on 198 children (87 boys and 111 girls). Among boys, high prenatal BPA exposure (highest quartile vs. the lowest three quartiles) was associated with significantly higher CBCL scores (more problems) on Emotionally Reactive [1.62 times greater; 95% confidence interval (CI): 1.13, 2.32] and Aggressive Behavior syndromes (1.29 times greater; 95% CI: 1.09, 1.53). Among girls, higher exposure was associated with lower scores on all syndromes, reaching statistical significance for Anxious/Depressed (0.75 times as high; 95% CI: 0.57, 0.99) and Aggressive Behavior (0.82 times as high; 95% CI: 0.70, 0.97). Conclusion: These results suggest that prenatal exposure to BPA may affect child behavior, and differently among boys and girls.
Information Warfare-Worthy Jamming Attack Detection Mechanism for Wireless Sensor Networks Using a Fuzzy Inference System

The proposed mechanism for jamming attack detection for wireless sensor networks is novel in three respects: firstly, it upgrades the jammer to include versatile military jammers; secondly, it graduates from the existing node-centric detection system to the network-centric system making it robust and economical at the nodes, and thirdly, it tackles the problem through fuzzy inference system, as the decision regarding intensity of jamming is seldom crisp. The system with its high robustness, ability to grade nodes with jamming indices, and its true-detection rate as high as 99.8%, is worthy of consideration for information warfare defense purposes.
Beden Eğitimi Öğretmeni Adaylarının Öğretmenlik Mesleğine İlişkin Tutumları ile Öz Yeterlikleri Arasındaki İlişki

Bu calismanin amaci, Bartin Universitesinde ogrenim goren beden egitimi ogretmeni adaylarinin ogretmenlik meslegine iliskin tutumlari ile oz yeterlikleri arasindaki iliskinin kisisel bilgiler ve konuyla ilgili olcekler kullanilarak belirlenmesi ve tartisilmasidir. Bu amacla calismanin evrenini, Bartin Universitesi Beden Egitimi ve Spor Yuksekokulu Beden Egitimi ve Spor Ogretmenligi Bolumunde ogrenim goren ogrenciler, orneklemini ise Bartin Universitesi Beden Egitimi ve Spor Yuksekokulu Beden Egitimi ve Spor Ogretmenligi Bolumunde ogrenim goren ve hazir uygulanabilir grup yoluyla secilen 217 gonullu ogrenci olusturmaktadir. Olceklerin orneklem grubuna uygulanmasi icin arastirmaci ogrencilerle gorusmek suretiyle olcegi uygulatmis, boylelikle birinci elden bilgilendirme de yapmistir. Beden egitimi ogretmeni adaylarinin ogretmenlik meslegine iliskin tutumlari ile oz yeterlikleri arasindaki iliskiye ait arastirma grubunun cinsiyet degiskenine gore frekans ve yuzde dagilimlari acisindan arastirma grubunu olusturan toplam 217 katilimcinin 142’si erkek, 75’i kadindir (Xyas=21.54±2.50). Yapilan bu calisma sonucunda arastirma grubunun oz yeterlik puan ortalamalari cinsiyet, sinif, calisma durumu (is deneyimi), aile geliri ve spor yapma durumu degiskenleri acisindan incelendiginde istatistiksel olarak anlamli bir farklilik bulunamamistir. Elde edilen bulgulara gore arastirma grubunun yas ve spor yili degiskenlerine gore oz yeterlikleri incelendiginde istatistiksel olarak anlamli bir iliski tespit edilememistir. Arastirma grubunun ogretmenlik meslegine iliskin tutumlarinin puan ortalamalari cinsiyet, sinif, calisma durumu (is deneyimi), aile geliri, spor yapma durumu degiskeni acisindan incelendiginde istatistiksel olarak anlamli bir farklilik bulunamamistir. Elde edilen bulgulara isiginda arastirma grubunun yas degiskenine gore ogretmenlik meslegine iliskin tutumlari incelendiginde istatistiksel olarak anlamli bir iliski tespit edilmemis iken spor yili degiskenine gore ogretmenlik meslegine iliskin tutumlari incelendiginde ise istatistiksel olarak anlamli bir iliski tespit edilmistir. Bu sonuca gore arastirma grubunun spor yili degiskeni ile ogretmenlik meslegine iliskin tutumlari arasinda dusuk duzeyde pozitif bir iliski bulunmaktadir. Yapilan bu calisma sonucunda arastirma grubunun ogretmenlik meslegine iliskin tutumlari ile oz yeterlikleri arasindaki iliski incelendiginde istatistiksel olarak anlamli bir iliski bulunamamistir.
The linear dependence of ventricular repolarization variability on heart rate variability in head-down bed rest studies

Head down bed rest as Earth-based study for simulating microgravity affects cardiovascular system. However the consequences for the health of this experiment during and at recovery are still under research and in particular ventricular repolarization (VR) effects are not well known. VR dysfunctions could lead to cardiac arrhythmias and eventually to sudden cardiac death. Interactions of VR variability with heart rate variability (HRV) was used as proarrhythmic marker. In this study, three VR beat-to-beat indices extracted from ECG signals as QT, QTp (QRS on-set to T wave peak) and Tpe (peak to end of T wave) were measured and their variabilities studied. ARARX modeling was the tool used to estimate the VR variability fraction driven by HRV at different time periods: PRE, during head down bed rest (5-day & 21-day periods) and POST. We found significant differences (p-values <; 0.01) comparing the repolarization variability content driven by heart rate in all VR series at PRE versus during BR microgravity conditions and after in both cases of study. Head down bed rest test increases the amount of linear dependency of VR variability and HRV. Results tend to evidence a slow recovery capacity for all VR variability after simulated microgravity exposition, being more notable for 21-day HDBR.
Closed-Form Inverse Kinematics for Continuum Manipulators

This paper presents a novel, analytical approach to solving inverse kinematics for multi-section continuum robots, defined as robots composed of a continuously bendable backbone. The problem is decomposed into several simpler subproblems. First, this paper presents a solution to the inverse kinematics problem for a single-section trunk. Assuming endpoints for all sections of a multi-section trunk are known, this paper then details applying single-section inverse kinematics to each section of the multi-section trunk by compensating for the resulting changes in orientation. Finally, an approach which computes per-section endpoints given only a final-section endpoint provides a complete solution to the multi-section inverse kinematics problem. The results of implementing these algorithms in simulation and on a prototype continuum robot are presented and possible applications discussed.
An experimental study of Multi-Objective Evolutionary Algorithms for balancing interpretability and accuracy in fuzzy rulebase classifiers for financial prediction

This paper examines the advantages of simple models over more complex ones for financial prediction. This premise is examined using a genetic fuzzy framework. The interpretability of fuzzy systems is oftentimes put forward as a unique advantageous feature, sometimes to justify effort associated with using fuzzy classifiers instead of alternatives that can be more readily implemented using existing tools. Here we investigate if model interpretability can provide further benefits by realizing useful properties in computationally intelligent systems for financial modeling. We test an approach for learning momentum based strategies that predict price movements of the Bombay Stock Exchange (BSE). The paper contributes an experimental evaluation of the relationship between the predictive capability and interpretability of fuzzy rule based systems obtained using Multi-Objective Evolutionary Algorithms (MOEA.)
Curriculum integration in the senior secondary school: a case study in a national assessment context

Abstract This paper considers curriculum integration in the secondary school context and investigates the claims made that it can enhance learning outcomes for students. I argue that curriculum integration should be utilized not as a main means of curricular delivery but as a supplementary opportunity to put disciplinary knowledge to use in certain, well-planned contexts. In other words, disciplinary learning comes first and is then deepened through application in an interdisciplinary context. This argument is illustrated through a case study of a new ‘21st Century’ secondary school where interdisciplinarity is a cornerstone of the school’s philosophy. Methods for the study included weekly observations, interviews, focus groups and a survey. I conclude by suggesting that teachers require further time and assistance to develop programmes and evaluative criteria to ensure learning moves beyond thematically generated common sense knowledge, towards interdisciplinary insights.
Multiple model framework of adaptive extended kalman filtering for predicting vehicle location

A multiple-model framework of adaptive extended Kalman filters (EKF) for predicting vehicle position with the aid of Global Positioning System (GPS) data is proposed to improve existing collision avoidance systems. A better prediction model for vehicle positions provides more accurate collision warnings in situations that current systems can not handle correctly. The multiple model adaptive estimation system (MMAE) algorithm is applied to the integration of GPS measurements to improve the efficiency and performance. This paper evaluates the multiple-model system in different scenarios and compares it to other systems before discussing possible improvements by combining it with other systems for predicting vehicle location
Design and Implementation of Monophones and Triphones-Based Speech Recognition Systems for Voice Activated Telephony

Speech recognition is the ability of a machine or program to convert spoken words into its equivalent text form. Nowadays, most recognition systems use Hidden Markov Models for modeling the spoken utterances. In this paper we have implemented two speaker independent speech recognition systems which include all the words required for dialing a phone. The systems contain 42 words including digits from zero to nine and also include names of 20 persons. A total of 16,800 utterances have been used for training each system. The two systems are able to recognize continuous speech and it is implemented with the help of monophones and triphones using HTK. Experimental results show an accuracy of 74.11% for monophones based models and 93.77% for triphones based models. Index Terms HMM, HTK, Monophones, Triphones, Mel Frequency Cepstral Coefficient (MFCC).
THE ARTIFICIAL EVOLUTION OF CONTROL

Recently there have been a number of proposals for the use of artiicial evolution as a radically new approach to the development of robot control systems. This paper explains and justiies the evolutionary robotics methodology developed and used at Sus-sex University. Results are presented from research into the concurrent evolution of dynamical network controllers and visual sensor morphologies for an autonomous mobile robot. Successful experiments to evolve robot controllers directly in hardware, thus allowing advantage to be taken of intrinsic silicon physics, are also discussed. The implications of recent work in using high quality engineering simulations to evolve control systems for real robots will are covered.
Discrete Time Homogeneous and non-Homogeneous semi-Markov Reliability Models.∗

In this paper, we extend to our knowledge, for the first case, some reliability results obtained using homogeneous semi-Markov processes to the case of non-homogenous semi-Markov modelisation. Moreover, we apply some of our preceding results to give the numerical solutions and so the possibility to treat real life problems for which non-homogeneity in time is important.
Molecular Evolution of the Infrared Sensory Gene TRPA1 in Snakes and Implications for Functional Studies

TRPA1 is a calcium ion channel protein recently identified as the infrared receptor in pit organ-containing snakes. Therefore, understanding the molecular evolution of TRPA1 may help to illuminate the origin of “heat vision” in snakes and reveal the molecular mechanism of infrared sensitivity for TRPA1. To this end, we sequenced the infrared sensory gene TRPA1 in 24 snake species, representing nine snake families and multiple non-snake outgroups. We found that TRPA1 is under strong positive selection in the pit-bearing snakes studied, but not in other non-pit snakes and non-snake vertebrates. As a comparison, TRPV1, a gene closely related to TRPA1, was found to be under strong purifying selection in all the species studied, with no difference in the strength of selection between pit-bearing snakes and non-pit snakes. This finding demonstrates that the adaptive evolution of TRPA1 specifically occurred within the pit-bearing snakes and may be related to the functional modification for detecting infrared radiation. In addition, by comparing the TRPA1 protein sequences, we identified 11 amino acid sites that were diverged in pit-bearing snakes but conserved in non-pit snakes and other vertebrates, 21 sites that were diverged only within pit-vipers but conserved in the remaining snakes. These specific amino acid substitutions may be potentially functional important for infrared sensing.
Confidence Measures for Turkish Call Center Conversations

Automatic speech recognition accuracies of call-canter conversations are still below intended levels due to harsh conditions such as channel distortions, external noises, coarticulated speech, etc. Agglutinative and free word order nature of Turkish degrades the recognition performances further; therefore the usage of confidence measures (CMs) is inevitable to retrieve correct information from the calls. In this paper, two conversational CMs, namely speech overlap ratio and opposite party energy level, are proposed, and tested together with single-channel confidence measures on Turkish stereo call center recordings. Experimental results show that conversational CMs improve the rating accuracies of the utterances with respect to their recognition rates.
RNA sampling and crystallographic refinement using Rappertk

Background. Dramatic increases in RNA structural data have made it possible to recognize its conformational preferences much better than a decade ago. This has created an opportunity to use discrete restraint-based conformational sampling for modelling RNA and automating its crystallographic refinement. Results. All-atom sampling of entire RNA chains, termini and loops is achieved using the Richardson RNA backbone rotamer library and an unbiased distribution for glycosidic dihedral angle. Sampling behaviour of Rappertk on a diverse dataset of RNA chains under varying spatial restraints is benchmarked. The iterative composite crystallographic refinement protocol developed here is demonstrated to outperform CNS-only refinement on parts of tRNA(Asp) structure. Conclusion. This work opens exciting possibilities for further work in RNA modelling and crystallography.
Reformulation of Telugu web query using word semantic relationships

Use of Internet becomes more popular in India to avail the information needs. A major area of Information browsing includes Education, Medical, Agriculture, Geographical, Business and other social domains. Availability of electronic documents for Indian Language is growing day by day. The people living throughout India speak different languages. The government of India has given "languages of the 8th Schedule" official status for 22 languages. Compare to European languages and other Indian languages, processing of Telugu language electronic documents is more difficult in nature. This is due to multi --- encoding formats of the text. Indian languages are encoded using Unicode, ISCII. To fasten the retrieval process the Unicode or ISCII is need to be converted into simple and standard encoding which makes Information Retrieval as easy task. Once the information processing system is build for a mono-lingual, it is the base to go for Multi-lingual and Cross --- lingual information processing. In Information Retrieval process users expects exact results for the given query. It depends on the vocabulary expertization of the end user in building the root query. Word mismatch is common problem of all languages in Information Retrieval process. Query Expansion gives a solution to the word mismatch problem. In Query Expansion the top ranked documents are used to expand the query terms. Sometimes user need to judge the relevance of the expanded query to iterate search. The relevance judgment of the user depends on the knowledge (i.e Language knowledge to describe the con text of the query) of the user. If the con cept hierarchy is properly defined, then user involvement is void in this scenario. This can be easily test on English language, but applying Query Reformulation technique directly on Indian languages is not stands good, because the nature of Indian languages is not simple like English. The Paper is aimed to reduce the mismatch between user query and retrieved documents by using semantic relationships between query terms and document terms. To test the proposed model, Telugu language, one of the Indian languages is taken as a case study. True translation from English to Telugu and vice versa is not possible due to high word conflation in Indian languages. This paper is an attempt to adopt Semantic Network with semantic relationships between terms of a query to reformulate and iterate the search. Method of Relevance Feedback improves recall without compromising precision, but it works well on limited corpus. Reformulation of query by embedding WordNet, ConceptNet relationsh ips gave better results, but great fall of precision is observed. Comparison between initial query test results and reformulated query search results are made in result analysis.
A framework for recognizing and segmenting sign language gestures from continuous video sequence using boosted learning algorithm

The problem of vision-based sign language recognition, which is used to translate signs to English sentence, is addressed in this paper. A fully automatic system to recognize signs that starts with breaking up signs into manageable subunits is proposed. A framework for segmenting and tracking skin objects from signing videos is described. A boosting algorithm to learn a subset of weak classifiers for extracted features to combine them into a strong classifier for each sign is then applied. A joint learning strategy to share subunits across sign classes is adopted, which leads to a more efficient classification of sign gestures. Experimental results shown by the system demonstrate that the proposed approach is promising to build an effective and scalable system on real-world hand gesture recognition from continuous video sequences.
The Variational Structure of Disparity and Regularization of 4D Light Fields

Unlike traditional images which do not offer information for different directions of incident light, a light field is defined on ray space, and implicitly encodes scene geometry data in a rich structure which becomes visible on its epipolar plane images. In this work, we analyze regularization of light fields in variational frameworks and show that their variational structure is induced by disparity, which is in this context best understood as a vector field on epipolar plane image space. We derive differential constraints on this vector field to enable consistent disparity map regularization. Furthermore, we show how the disparity field is related to the regularization of more general vector-valued functions on the 4D ray space of the light field. This way, we derive an efficient variational framework with convex priors, which can serve as a fundament for a large class of inverse problems on ray space.
Design and implementation of a soft-decision decoder for Cortex codes

Cortex codes are a family of rate-1/2 self-dual systematic linear block codes with good distance properties. This paper investigates the challenging issue of designing an efficient soft-decision decoder for Cortex codes. A dedicated algorithm is introduced that takes advantage of the particular structure of the code to simplify the decoding. Simulation results show that the proposed algorithm achieves an excellent trade-off between performance and complexity for short Cortex codes. A decoder architecture for the (32,16,8) Cortex code based on the (4,2,2) Hadamard code has been successfully designed and implemented on FPGA device. To our knowledge, this is the first efficient digital implementation of a soft-decision Cortex decoder.