Miracle-dz/UniFAR-FTUs huggingface dataset:
Gray Matter Volume of the Lingual Gyrus Mediates the Relationship between Inhibition Function and Divergent Thinking

Although previous research provides converging evidence for the role of posterior regions of the brain (including temporal, occipital, and parietal regions) involved in inhibition on creative thinking, it remains unclear as to how these regions influence individual differences in creative thinking. Thus, we explored the relationship between posterior regions (i.e., hippocampal, parahippocampal, lingual gyrus, precuneus, and cuneus), inhibition function, and divergent thinking (DT) in 128 healthy college students. The results revealed that lower inhibition was associated with larger gray matter volume (GMV) in the lingual gyrus, which in turn was associated with higher DT. In addition, GMV in the lingual gyrus mediated the association between inhibition and DT. These results provide new evidence for the role of inhibition in creative thinking. Inhibition may affect the amount of information stored in long-term memory, which, in turn influences DT.
A STUDY ON ACCOUNTABILITY AND PERCEIVED AUTONOMY SUPPORT AMONG PRE-UNIVERSITY COLLEGE TEACHERS

ABSTRACT Accountability of Teachers referred to as teacher accountability in educational literature is a multi-dimensional concept consisting of teacher participation in school decision making. It further focuses on what is best for the student and the profession of teaching. Self-determination theory postulates that when teachers perceive an autonomy supportive work climate which satisfies their three core psychological needs, (Competence, Autonomy and Relatedness) they experience a feeling of wellness and belongingness to the institution and are energized to exert extra effort in all the activities of the institution they engage in. The present study on Accountability and Perceived Autonomy Support among Pre-university College Teachers undertaken by the investigator focused on the relationship between Accountability of Teachers and Perceived Autonomy Support among Pre-university college teachers of Bangalore north and south belonging to three types of management such as government, private aided and private unaided. The aim of this study was to find out whether there is any relationship between Accountability of Teachers and Perceived Autonomy Support. The sample of the study consisted of 392 pre-university college teachers (both male and female) of three types of colleges; namely government, private aided and private unaided. The results of the study show that there is a significant relationship between Accountability of Teachers and Perceived Autonomy Support among pre-university college teachers. Further female teachers are more accountable than their male counterparts and Married teachers are found be more accountable than unmarried teachers. It was also found that there is a significant difference in the Competence dimension of Perceived Autonomy Support among pre-university college teachers belonging to three types of management and the Private Aided pre-university college teachers have a higher level of Competence (dimension of Perceived Autonomy Support) compared to Private unaided pre-university college teachers. Private Aided Pre-university college teachers have higher level of Relatedness (dimension of Perceived Autonomy Support) as compared to Private unaided College Teachers. These findings give a clear indication to principals and administrators of private unaided pre-university colleges regarding the imperative need to implement appropriate strategies in order to enhance perceived autonomy support of their teachers. Key words: Accountability of Teachers, Perceived Autonomy Support, Pre-university college teachers
Speech Recognition using Acoustic Landmarks and Binary Phonetic Feature Classifiers October 31 , 2003

In spite of decades of research, Automatic Speech Recognition (ASR) is far from reaching the goal of performance close to Human Speech Recognition (HSR). One of the reasons for unsatisfactory performance of the state-of-the-art ASR systems, that are based largely on Hidden Markov Models (HMMs), is the inferior acoustic modeling of low level or phonetic level linguistic information in the speech signal. An acoustic-phonetic approach to ASR, on the other hand, explicitly targets linguistic information in the speech signal. But an acoustic phonetic system that carries out large ASR speech recognition tasks, for example, connected word or continuous speech recognition, does not exist. We propose a probabilistic and statistical framework for ASR based on the knowledge of acoustic phonetics for connected word ASR. The proposed system is based on the idea of representation of speech sounds by bundles of binary valued articulatory phonetic features. The probabilistic framework requires only binary classifiers of phonetic features and the knowledge based acoustic correlates of the features for the purpose of connected word speech recognition. We explore the use of Support Vector Machines (SVMs) for binary phonetic feature classification because of the favorable properties well suited to our recognition task that SVMs offer. In the proposed method, probabilistic segmentation of speech is obtained using SVM based classifiers of manner phonetic features. The linguistically motivated landmarks obtained in each segmentation is used for classification of source and place phonetic features. Probabilistic segmentation paths are constrained using Finite State Automata (FSA) for isolated or connected word recognition. The proposed method could overcome the disadvantages encountered by the early acoustic-phonetic knowledge based systems, that led the ASR community to switch to ASR systems highly dependent on statistical pattern analysis methods.
Big Data Analysis: Apache Storm Perspective

— the boom in the technology has resulted in emergence of new concepts and challenges. Big data is one of those spoke about terms today. Big data is becoming a synonym for competitive advantages in business rivalries. Despite enormous benefits, big data accompanies some serious challenges and when it comes to analyzing of big data, it requires some serious thought. This study explores Big Data terminology and its analysis concepts using sample from Twitter data with the help of one of the most industry trusted real time processing and fault tolerant tool called Apache Storm.
Relative risk of listeriosis in Foodborne Diseases Active Surveillance Network (FoodNet) sites according to age, pregnancy, and ethnicity.

BACKGROUND Quantitative estimates of the relative risk (RR) of listeriosis among higher-risk populations and a nuanced understanding of the age-specific risks are crucial for risk assessments, targeted interventions, and policy decisions. METHOD The RR of invasive listeriosis was evaluated by age, pregnancy status, and ethnicity using 2004-2009 data from the Foodborne Diseases Active Surveillance Network (FoodNet). Nonparametric logistic regression was used to characterize changes in risk with age and ethnicity. Adjusted RRs and 95% confidence intervals (CIs) were evaluated using negative binomial generalized linear models. RESULTS Among non-pregnancy-associated cases, listeriosis incidence rates increased gradually with age (45-59 years: RR, 4.7; 95% CI, 3.3-6.8; >85 years: RR, 53.8; 95% CI, 37.3-78.9; reference: 15-44 years). The RR was significantly higher for Hispanics than for non-Hispanics (RR, 1.8; 95% CI, 1.3-2.5). Among women of reproductive age (15-44 years), pregnant women had a markedly higher listeriosis risk (RR, 114.6; 95% CI, 68.9-205.1) than nonpregnant women. The RR was higher for Hispanic than non-Hispanic women, regardless of pregnancy status, and this increased during the study period (2004-2006: RR, 1.9; 95% CI, 1.0-3.3; 2007-2009: RR, 4.8; 95% CI, 3.1-7.1). CONCLUSIONS This study quantifies the increases in risk of listeriosis among older persons, pregnant women, and Hispanics in the United States. Additional research is needed to better describe the independent effects of age on risk while accounting for underlying conditions. These estimates are needed both to optimize risk assessment models and to inform targeted interventions and policy decisions.
Information, Relevance and Social Decisionmaking: Applications to Non-truth-conditional Semantics

Compressed Abstract: This paper submits an approach to broadly non-truth-conditional aspects of meaning in natural language which interprets`pragmatics' substantively: in the way of C.S. Peirce and F.P. Ramsey, as a synonym for decision-theory. We outline (i) basic assumptions, (ii) some relations to other approaches, (iii) a range of results wide enough to justify the termàpproach'. A key notion is`relevance', explicated and related to information in the traditional, stochastic way.
Modeling the Interaction between Cumulus Convection and Linear Gravity Waves Using a Limited-Domain Cloud System–Resolving Model

Abstract A limited-domain cloud system–resolving model (CSRM) is used to simulate the interaction between cumulus convection and two-dimensional linear gravity waves, a single horizontal wavenumber at a time. With a single horizontal wavenumber, soundings obtained from horizontal averages of the CSRM domain allow the large-scale wave equation to be evolved, and thereby its interaction with cumulus convection is modeled. It is shown that convectively coupled waves with phase speeds of 8–13 m s−1 can develop spontaneously in such simulations. The wave development is weaker at long wavelengths (>∼10 000 km). Waves at short wavelengths (∼2000 km) also appear weaker, but the evidence is less clear because of stronger influences from random perturbations. The simulated wave structures are found to change systematically with horizontal wavelength, and at horizontal wavelengths of 2000–3000 km they exhibit many of the basic features of the observed 2-day waves. The simulated convectively coupled waves develop wit.
Social Determinants of Suicides in the Czech Republic between 1995 and 2010

The text is concerned with suicides in the Czech Republic. It seeks to determine which social variables, and to what extent, have affected suicidal behaviour since 1989. The authors draw on Durkheim’s theory that society prevents suicidal tendencies. They formulate six hypotheses to account for the effects of social variables (year, sex, age, education, and marital status) on suicide rates, which they test using data from 1995 to 2010. Their findings show that time weakens the odds for committing suicides. Regardless of the time, women and people who are young, more educated, and living in a marriage face the lowest risk of suicide. That marriage works as a shield against suicide is especially true for men (its protective function for women is significantly lower). In the period observed, there was a relative increase in the effect of two social variables: middle age (45–69 years) and lower education. The structure of variables explaining suicide rates changed during the time period observed.
Screening Auxin Response, In Vitro Culture Aptitude and Susceptibility to Agrobacterium-Mediated Transformation of Italian Commercial Durum Wheat Varieties

The development of a robust Agrobacterium-mediated transformation protocol for a recalcitrant species like durum wheat requires the identification and optimization of factors affecting T-DNA delivery and plant regeneration. The purpose of this research was to compare the behavior of diverse durum wheat genotypes during in vitro culture and Agrobacterium tumefaciens-mediated transformation, using immature embryos as explants. Apart from plant genotype, two of the main influencing factors for a successful genetic transformation have been examined here, i.e., auxin source (Dicamba and 2,4-D) and duration of the pre-culture period (one, seven and 21 days). The addition of Dicamba to the media in combination with seven days pre-cultivation resulted in a general enhancement of T-DNA delivery for most of the analyzed cultivars, as revealed by β-glucuronidase (GUS) histochemical assay. Although all genotypes were able to produce calli, significant differences were detected in regeneration and transformation efficiencies, since only two (Karalis and Neolatino) out of 14 cultivars produced fertile transgenic plants. The estimated transformation efficiencies were 6.25% and 1.66% for Karalis and Neolatino, respectively, and χ2 analysis revealed the stable integration and segregation of the gus transgene in T1 and T2 progenies. This research has demonstrated that, among the influencing factors, genotype and auxin type play the most important role in the success of durum wheat transformation.
Reducing Photon-Mapping Bandwidth by Query Reordering

Photon mapping places an enormous burden on the memory hierarchy. Rendering a 512 x 512 image of a simple scene can require more than 196 Gbytes of raw bandwidth to the photon map data structure. This bandwidth is a major obstacle to real-time photon mapping. This paper investigates two approaches for reducing the required bandwidth: 1) reordering the kNN searches and 2) cache conscious data structures. Using a Hilbert curve reordering, we demonstrate an experimental lower bound of 15 Mbytes of bandwidth for the same scene. Unfortunately, this improvement of four orders of magnitude requires a prohibitive amount of intermediate storage. We introduce two novel cost-effective algorithms that reduce the bandwidth by one order of magnitude. Scenes of different complexities are shown to exhibit similar reductions in bandwidth. We explain why the choice of data structure does not achieve similar reductions. We also examine the interaction of query reordering with two photon map acceleration techniques, importance sampling, and the irradiance cache. Query reordering exploits the additional coherence that arises from the use of importance sampling in scenes with glossy surfaces. Irradiance caching also benefits from query reordering, even when complex surface geometry reduces the effectiveness of the irradiance cache.
Pessimistic Explanatory Style in the Historical Record: CAVing LBJ, Presidential Candidates, and East Versus West Berlin

" The habitual way people explain causes (explanatory style) as assessed by questionnaire has been used to predict depression, achievement, and health, with a pessimistic style predicting poor outcomes. Because some individuals whose behavior is of interest cannot take questionnaires, their explanatory style can be assessed by blind, reliable content analysis of verbatim explanations (CAVE) from the historical record. We discuss three examples of CAVing archival material First, shifts to a more optimistic style in Lyndon Johnson's press conferences predicted bold, risky action during the Vietnam War, whereas shifts to pessimism predicted passivity. Second, analyses of presidential candidates" nomination acceptance speeches from 1948 to 1984 showed that candidates who were more pessimistically ruminative lost 9 of the 10 elections. Third, explanatory style and its relation to depressive signs was considered at a societal level. There were more behavioral signs consistent with depression among workmen in East Berlin than in West Berlin bars. This finding corresponded to a comparatively more pessimistic explanatory style in East Berlin newspaper reports concerning the 1984 Winter Olympics. We suggest that pessimism and its consequences can be quantified and compared, not only in contemporary individuals but also across time and culture. Can pessimism and its consequences be measured across historical periods and cultures? One tool for measuring pessimism is the habitual way people explain the events that befall them, their "explanatory style" as found in archival documents. One way to measure the consequences of pessimism is to observe the symptoms of learned helplessness--passivity, poor achievement, and depressive signs--as they are found in the historical record. With these tools we can try both to test theories of explanatory style and to predict real-world behavior over historical periods and across cultures. In this article, we first present the theoretical background and describe our tools. In doing so, we detail a new method, the content analysis of verbatim explanations (CAVE), which allows blind, reliable ratings of archival material for explanatory style. Then we present three brief examples: President Johnson and the Vietnam War, prediction of who will win modern presidential elections, and pessimism in East and West Berlin. Our story begins with explanatory style and its relation to learned helplessness.
Does Circadian Disruption Play a Role in the Metabolic–Hormonal Link to Delayed Lactogenesis II?

Breastfeeding improves maternal and child health. The American Academy of Pediatrics recommends exclusive breastfeeding for 6 months, with continued breastfeeding for at least 1 year. However, in the US, only 18.8% of infants are exclusively breastfed until 6 months of age. For mothers who initiate breastfeeding, the early post-partum period sets the stage for sustained breastfeeding. Mothers who experience breastfeeding problems in the early post-partum period are more likely to discontinue breastfeeding within 2 weeks. A major risk factor for shorter breastfeeding duration is delayed lactogenesis II (DLII; i.e., onset of milk “coming in” more than 72 h post-partum). Recent studies report a metabolic–hormonal link to DLII. This is not surprising because around the time of birth the mother’s entire metabolism changes to direct nutrients to mammary glands. Circadian and metabolic systems are closely linked, and our rodent studies suggest circadian clocks coordinate hormonal and metabolic changes to support lactation. Molecular and environmental disruption of the circadian system decreases a dam’s ability to initiate lactation and negatively impacts milk production. Circadian and metabolic systems evolved to be functional and adaptive when lifestyles and environmental exposures were quite different from modern times. We now have artificial lights, longer work days, and increases in shift work. Disruption in the circadian system due to shift work, jet-lag, sleep disorders, and other modern life style choices are associated with metabolic disorders, obesity, and impaired reproduction. We hypothesize that DLII is related to disruption of the mother’s circadian system. Here, we review literature that supports this hypothesis, and describe interventions that may help to increase breastfeeding success.
GLCM based adaptive crossed reconstructed (ACR) k-mean clustering hand bone segmentation

With the advent of digital medical imaging, implementation of automated image processing has been explored for a number of years. Nevertheless, to date, exploration in the computer-aided digital medical imaging processing remains confronting with numerous challenges and unsolved technical issues. Radiographic hand bone segmentation is one of them. The most common bones used in skeletal age maturity assessment are the hand and wrist. With the intent of constructing an automated assessment system which can significantly enhances the efficiency of the assessment, the technique of hand and wrist bone segmentation is the first and most crucial step before proceeding to the bone age analysis. However, it is difficult to segment the bone from the soft tissue area in radiograph. In this paper, a novel method of GLCM based adaptive crossing reconstruction (ACR) k-mean clustering method is proposed to segment the hand bone from the soft tissue area in radiograph. This approach start by dividing the image into several vertical bands and into several horizontal bands subsequently, the pixels of each region are k-means clustered with the feature of pixel's intensity followed by performing the GLCM texture analysis. Eventually, the different sections will be reconstructed based on the texture analysis result. By dividing the images into multiple regions and reconstructed again based on texture analysis, the bone can be segmented from soft tissue region more effectively compared to global segmentation. However the result is not optimized due to the reason that there are a lot of parameters that can be altered to obtain better result at the price of computational performance.
Exploiting partially defective LUTs: Why you don't need perfect fabrication

Shrinking integrated circuit feature sizes lead to increased variation and higher defect rates. Prior work has shown how to tolerate the failure of entire LUTs and how to tolerate failures and high variation in interconnect. We show how to use LUTs even when they are partially defective - a form of fine-grained defect tolerance. We characterize the defect tolerance of a range of mapping strategies for defective LUTs, including LUT swapping in a cluster, input permutation, input polarity selection, defect-aware packing, and defect-aware placement. By tolerating partially defective LUTs, we show that, even without allocating dedicated spare LUTs, it is possible to achieve near perfect yield with cluster local remapping when roughly 1% of the LUT multiplexers fail to switch. With full, defect-aware placement, this can increase to 10-25% with just a few extra rows and columns. In contrast, substitution of perfect LUTs to dedicated spares only tolerates failure rates of 0.01-0.05%.
Accurate FMCW radar-based indoor localization system

An accurate ranging system based on FMCW (Frequency Modulated Continuous Wave) Radar is presented. The system ensures a centimetre precision even in environments with high multipath, such as warehouses packed with metallic objects or extremely dusty sites where conventional RF, laser, ultrasonic or video technologies present severe limitations. The proposed solution has been experimentally applied in Automatic Guided Vehicle for warehouses. The architecture of the system and the obtained results are presented in detail.
Information gateway for integrated pharmacogenomics data- IGIPD

The current challenge in drug discovery lies in developing personalized drugs as individual genetic makeup respond differently to a particular drug. There are enough evidences of adverse drug reactions because of genetic response towards drugs in drug therapy. The study of these relations between the human genomics and pharmacogenetics emerged into Pharmacogenomics. There are many publicly accessible pharmacogenomic data repositories having large, rapidly changing and complex data. These databases provide information about the drugs, their adverse reactions, chemical formula, information about metabolic pathways, drug targets, disease for which a particular drug is used etc. None of the existing pharmacogenomic databases carry the complete integrated information and hence there is a need to develop a database which integrates data from all the widely used databases.