Miracle-dz/UniFAR-FTUs huggingface dataset:
Duration and spectral based stress token generation for HMM speech recognition under stress

In this paper, we address the problem of isolated word recognition of speech under various stressed speaking conditions. The main objective is to formulate an alternate training algorithm for hidden Markov model recognition, which better characterizes actual speech production under stressed speaking styles such as slow, loud and Lombard (1911) effect. Without the need for collecting such stressed speech data. The novel approach is to first construct a previously suggested source generator model of word production employing knowledge of the statistical nature of duration and spectral variation of speech under stress. This is used in turn to produce simulated stressed speech training tokens from neutral tokens, and thus replace neutral data used in the recognizer training phase. The token generation training method is shown to improve isolated word recognition by 8% for slow speaking style, 14% for loud speaking style, and 24% for speech under Lombard effect when compared to neutral trained isolated word recognition. <<ETX>>
Comparison of various algorithms for recognizing short coding sequences of human genes

MOTIVATION Since the early 1980s of the twentieth century, there has been great progress in the development of computational gene-finding algorithms. Some problems, however, have not yet been solved currently. Recognizing short genes in prokaryotes and short exons in eukaryotes is one of such problems. The paper is devoted to assessing various algorithms, including those currently available and the new ones proposed here, in order to find the best algorithm to solve the issue. RESULTS The databases consisting of phase-specific coding and non-coding sequences of human genes with length of 192, 162, 129, 108, 87, 63 and 42 bp, respectively, have been established. Based on the databases and a standard benchmark, 19 algorithms were evaluated, which include the methods of Markov models with orders of 1 through 5, codon usage, hexamer usage, codon preference, amino acid usage, codon prototype, Fourier transform and 8 Z curve methods with various numbers of parameters. Consequently, the Z curve methods with 69 and 189 parameters are the best ones among them, based on the databases constructed here. In addition to the highest recognition accuracy confirmed by 10-fold cross-validation tests, the Z curve methods are much simpler computationally than the second best one, the fifth-order Markov chain model, in which 12 288 parameters are used. We hope that the Z curve methods presented in this paper would be beneficial to the further development of gene-finding algorithms. AVAILABILITY The programs of various Z curve methods are available on request.
Deviant gedrag en slachtofferschap onder jongens uit etnische minderheden I. (Deviant behaviour and victimization among boys of ethnic minorities I).

Uit het onderzoek komt naar voren dat de delinquentie onder allochtonen wat hoger is dan onder Nederlandse jongens van dezelfde leeftijd en met dezelfde socio-economische achtergrond. Twee zaken lijken van belang: Er zijn duidelijke verschillen tussen de allochtonen onderling. Onder Marokkaanse jongens is deze vertegenwoordiging - in vergelijking met Nederlandse jongens - groter dan onder Turkse en Surinaamse jongens. Men dient zich te realiseren dat de omvang van de problemen niet dezelfde is in alle etnische groepen. De relatief hoge percentages allochtone jongens met politiecontacten kunnen slechts gedeeltelijk verklaard worden uit hun relatief slechte socio-economische positie. Dit lijkt erop te wijzen dat andere factoren een rol spelen bij het al dan niet plegen van misdrijven. Dit zal in een volgend rapport aan de orde komen.
Visual working memory in health and disease

The ability of the nervous system to retain, manipulate and use visual information which is no longer present in the external environment contributes to intelligent behaviour. A new approach to studying visual working memory has led to re-evaluation of the nature of its limitations in keeping with a finite memory resource which is flexibly distributed across space according to attentional priority. Using a novel behavioural paradigm to study visual working memory precision for sequentially presented items, I demonstrate how the resolution with which healthy subjects recall simple objects changes dynamically with each new item in the sequence. Stochastic modelling of the distribution of responses suggested that memory for earlier objects in the sequence was especially prone to failure in integration of visual features, such as orientation and colour, into complete objects. Next, I examined how memory precision was affected by attentional selection according to the relative behavioural relevance of objects in a sequence, and explored the limitations in this filtering process and their relationship with performance on standard measures of memory and intelligence. The role of updating of non-spatial visual working memory across time was then examined in patients with visual neglect following right hemisphere stroke, revealing a profound non-spatial impairment in WM and its voluntary attentional control in neglect, when compared to stroke patients without neglect and healthy control subjects. Lesion analysis identified separable neural correlates of these deficits. Dopaminergic activity in the prefrontal cortex and basal ganglia has a pivotal and complex role in mediating and controlling working memory and attentional processes. In a randomised, double-blind, placebo controlled study, employing a replicated ABA N-of-1 randomised design, I tested the hypothesis that the dopamine agonist rotigotine improves visual neglect following right-hemisphere stroke. Rotigotine was associated with significant improvement in visual search, an effect that appears to have been mediated by an enhancement of selective, goal-directed attention. The medial temporal lobe (MTL) has an established role in supporting long-term memory processes, but its involvement in working memory has been debated recently. I studied visual working memory for sequentially presentated objects in four patients with MTL lesions and found that short-term memory can be compromised in such individuals. Overall, this thesis explores how visual working memory is updated dynamically across time according to attentional priority in health, how these processes are affected in patients with visual neglect following right hemisphere stroke and in those with medial temporal lesions, and how a dopamine agonist might ameliorate visual neglect by modulating selective attention. The thesis concludes with a brief discussion suggesting further research directions.
Detection of pulmonary nodules on chest x-ray images using R-CNN

Burdens of doctors for chest X-ray (CXR) examination have increased because number of X-ray images increases. Furthermore, since diagnosis is based on the experience and subjectivity of them, there is a possibility that a misdiagnosis may occur. Therefore, we performed Computer-Aided Diagnosis (CAD). In this study, we detected pulmonary nodules using R-CNN (Region with Convolutional Neural Network)[1] which is a kind of Deep Learning. First, we created CNN (Convolutional Neural Network) which classified data into classes of nodule opacities and nonnodule opacities. Next, we detected the object candidate regions from the chest X-ray images by Selective Search[2], and applied the CNN to the candidate regions to classify them and estimate the detailed position of the object. Thus, we propose a method to detect pulmonary nodules from the chest X-ray images.
Evaluating approaches to find exon chains based on long reads

Motivation Transcript prediction can be modelled as a graph problem where exons are modelled as nodes and reads spanning two or more exons are modelled as exon chains. PacBio third-generation sequencing technology produces significantly longer reads than earlier second-generation sequencing technologies, which gives valuable information about longer exon chains in a graph. However, with the high error rates of third-generation sequencing, aligning long reads correctly around the splice sites is a challenging task. Incorrect alignments lead to spurious nodes and arcs in the graph, which in turn lead to incorrect transcript predictions. Results We survey several approaches to find the exon chains corresponding to long reads in a splicing graph, and experimentally study the performance of these methods using simulated data to allow for sensitivity / precision analysis. Our experiments show that short reads from second-generation sequencing can be used to significantly improve exon chain correctness either by error-correcting the long reads before splicing graph creation, or by using them to create a splicing graph on which the long read alignments are then projected. We also study the memory and time consumption of various modules, and show that accurate exon chains lead to significantly increased transcript prediction accuracy. Availability The simulated data and in-house scripts used for this article are available at http://cs.helsinki. fi/u/aekuosma/exon_chain_evaluation_publish. tar.gz.
Voltage and frequency control of islanded microgrids: A plug-and-play approach

In this paper we propose a new decentralized control scheme for Islanded microGrids (ImGs) composed by the interconnection of Distributed Generation Units (DGUs). Local controllers regulate voltage and frequency at the Point of Common Coupling (PCC) of each DGU and they are able to guarantee stability of the overall ImG. The control design procedure is decentralized, since, besides two global scalar quantities, the synthesis of a local controller uses only information on the corresponding DGU and lines connected to it. Most important, our design procedure enables Plug-and-Play (PnP) operations: when a DGU is plugged in or out, only DGUs physically connected to it have to retune their local controllers. We study the performance of the proposed controllers simulating different scenarios in MatLab/Simulink and using indexes proposed in IEEE standards.
How I Learned to Stop Worrying and Love Flash Endurance

Flash memory in Solid-State Disks (SSDs) has gained tremendous popularity in recent years. The performance and power benefits of SSDs are especially attractive for use in data centers, whose workloads are I/O intensive. However, the apparent limited write-endurance of flash memory has posed an impediment to the wide deployment of SSDs in data centers. Prior architecture and system level studies of flash memory have used simplistic endurance estimates derived from datasheets to highlight these concerns. In this paper, we model the physical processes that affect endurance, which include both stresses to the memory cells as well as a recovery process. Using this model, we show that the recovery process, which the prior studies did not consider, significantly boosts flash endurance. Using a set of real enterprise workloads, we show that this recovery process allows for orders of magnitude higher number of writes and erases than those given in datasheets. Our results indicate that SSDs that use standard wear-leveling techniques are much more resilient under realistic operating conditions than previously assumed and serve to explain some trends observed in recent flash measurement studies.
Association between subjective social status and cardiovascular disease and cardiovascular risk factors: a systematic review and meta-analysis

Objective To determine the association between subjective social status (SSS), or the individual's perception of his or her position in the social hierarchy, and the odds of coronary artery disease (CAD), hypertension, diabetes, obesity and dyslipidaemia. Study Design Systematic review and meta-analysis. Methods We searched PubMed, MEDLINE, EMBASE, CINAHL, PsycINFO, SocINDEX, Web of Science and reference lists of all included studies up to October 2014, with a verification search in July 2015. Inclusion criteria were original studies in adults that reported odds, risk or hazard ratios of at least one outcome of interest (CAD, hypertension, diabetes, obesity or dyslipidaemia), comparing ‘lower’ versus ‘higher’ SSS groups, where SSS is measured on a self-anchoring ladder. ORs were pooled using a random-effects model. Results 10 studies were included in the systematic review; 9 of these were included in the meta-analysis. In analyses unadjusted for objective socioeconomic status (SES) measures such as income, education or occupation, the pooled OR comparing the bottom versus the top of the SSS ladder was 1.82 (95% CI 1.10 to 2.99) for CAD, 1.88 (95% CI 1.27 to 2.79) for hypertension, 1.90 (95% CI 1.25 to 2.87) for diabetes, 3.68 (95% CI 2.03 to 6.64) for dyslipidaemia and 1.57 (95% CI 0.95 to 2.59) for obesity. These associations were attenuated when adjusting for objective SES measures, with the only statistically significant association remaining for dyslipidaemia (OR 2.10, 95% CI 1.09 to 4.06), though all ORs remained greater than 1. Conclusions Lower SSS is associated with significantly increased odds of CAD, hypertension, diabetes and dyslipidaemia, with a trend towards increased odds of obesity. These trends are consistently present, though the effects attenuated when adjusting for SES, suggesting that perception of one's own status on a social hierarchy has health effects above and beyond one's actual income, occupation and education.
Trends in Health-Related Quality of Life Among Adolescents in the United States, 2001–2010

Health-related quality of life (HRQOL) measures are often used to track changes in population health, mostly among adults. Prompted by the recent US recession, we assessed trends in adolescent HRQOL by using cross-sectional data from the 2001–2010 National Health and Nutrition Examination Survey. Adolescents’ self-rated health and reported mental health declined significantly, especially among those in low-income families, but their physical health and activity limitation did not change. Because these HRQOL declines occurred at the end of the decade and especially among adolescents from low-income families, we conclude that these declines are consistent with recession effects and warrant further study.
Performance Evaluation and Analysis of Switching Algorithms in MIMO-OFDM System with Ideal and Non-Ideal CSI

In this paper we analyzed the bit error rate performance of a switching algorithm between spatial multiplex-ing and diversity for an OFDM MIMO system with ideal channel state information. The effect of channel estimation error was studied and we verified by simulations that the spatial multiplexing outperforms the switching algorithm. Given that the switching algorithm is based on the comparison of the channel matrix Demmel condition number to a threshold, its accuracy is compromised when channel estimation error in-creases. As a first intuitive solution, we proceeded to the adaptation of the threshold, but this didn’t lead to a pertinent improvement for the main reason that channel estimation errors did affect the MIMO techniques which use different constellation. Based on that, we proposed a new estimation technique that improved the bit error rate performance significantly.
GP-Select: Accelerating EM Using Adaptive Subspace Preselection

Abstract We propose a nonparametric procedure to achieve fast inference in generative graphical models when the number of latent states is very large. The approach is based on iterative latent variable preselection, where we alternate between learning a selection function to reveal the relevant latent variables and using this to obtain a compact approximation of the posterior distribution for EM. This can make inference possible where the number of possible latent states is, for example, exponential in the number of latent variables, whereas an exact approach would be computationally infeasible. We learn the selection function entirely from the observed data and current expectation-maximization state via gaussian process regression. This is in contrast to earlier approaches, where selection functions were manually designed for each problem setting. We show that our approach performs as well as these bespoke selection functions on a wide variety of inference problems. In particular, for the challenging case of a hierarchical model for object localization with occlusion, we achieve results that match a customized state-of-the-art selection method at a far lower computational cost.
Can Health Insurance Improve Employee Health Outcome and Reduce Cost? An Evaluation of Geisinger's Employee Health and Wellness Program

Objective: To evaluate the impact of a health plan–driven employee health and wellness program (known as MyHealth Rewards) on health outcomes (stroke and myocardial infarction) and cost of care. Methods: A cohort of Geisinger Health Plan members who were Geisinger Health System (GHS) employees throughout the study period (2007 to 2011) was compared with a comparison group consisting of Geisinger Health Plan members who were non-GHS employees. Result: The GHS employee cohort experienced a stroke or myocardial infarction later than the non-GHS comparison group (hazard ratios of 0.73 and 0.56; P < 0.01). There was also a 10% to 13% cost reduction (P < 0.05) during the second and third years of the program. The cumulative return on investment was approximately 1.6. Conclusion: Health plan–driven employee health and wellness programs similarly designed as MyHealth Rewards can potentially have a desirable impact on employee health and cost.
New non-invasive methods for assessing brain oxygenation and haemodynamics.

Hypoxic-ischaemic injury to the brain is the commonest cause of permanent neurodevelopmental disability in very preterm and other infants who survive after neonatal intensive care. Two new methods allow normal and abnormal oxidative metabolism to be investigated non-invasively in brain tissue. Magnetic resonance spectroscopy is used to measure the concentrations of important phosphorus compounds that are involved in energy metabolism— adenosine triphosphate, phosphocreatine and inorganic orthophosphate—and also to measure intracellular pH. Normal developmental changes with gestation have been defined and abnormalities indicating impaired oxidative phosphorylation detected in a range of conditions of suspected or proven hypoxic-ischaemic injury. Near infrared spectroscopy provides continuous cot-side information about cerebral oxygenation and haemodynamics. Quantitative measurements can be made of oxyhaemoglobin, deoxyhaemoglobin, oxidized cytochrome aa3 and various haemodynamic indices.
A conceptual opportunity-based framework to mitigate the insider threat

The aim of this paper is to provide a conceptual framework to mitigate the insider threat from an opportunity-based perspective. Although motive and opportunity are required to commit maleficence, this paper focuses on the concept of opportunity. Opportunity is more tangible than motive, hence it is more pragmatic to reflect on opportunity-reducing measures. Opportunity theories from the field of criminology are considered to this end. The derived framework highlights several areas of research and may assist organisations in designing controls that are situationally appropriate to mitigate insider threat. Current information security countermeasures are not designed from an opportunity-reducing perspective.
Agent's actions as a classification criteria for the state space in a learning from rewards system

We focus in this paper on the problem of learning an autonomous agent's policy when the state space is very large and the set of actions available is comparatively short. To this end, we use a non-parametric decision rule (concretely, a nearest-neighbour strategy) in order to cluster the state space by means of the action that leads to a successful situation. Using an exploration strategy to avoid greedy behaviour, the agent builds clusters of positively-classified states through trial and error learning. In this paper, we implement a 3D synthetic agent which plays an ‘avoid the asteroid’ game that suits our assumptions. Using as the state space a feature vector space extracted from a visual navigation system, we test two exploration strategies using the trial and error learning method. This experiment shows that the agent is a good classifier over the state space, and will therefore show good behaviour in its synthetic world.
Lead, Calcium Uptake, and Related Genetic Variants in Association with Renal Cell Carcinoma Risk in a Cohort of Male Finnish Smokers

Background: Lead is classified as a probable human carcinogen. However, its role in renal cell cancer (RCC) has not been established. Calcium and vitamin D may off-set toxicity in vivo. Methods: In this nested case–control study, whole blood lead, total serum calcium, and serum 25-hydroxyvitamin D levels were measured in blood drawn prior to diagnosis among male smokers participating in the Alpha-Tocopherol, Beta-Carotene Cancer Prevention Study. Single-nucleotide polymorphisms (SNP) in five genes (CALB1, TRPV5, TRPV6, VDR, and ALAD) related to lead toxicity or calcium transport were genotyped. Logistic and linear regressions were used to determine RCC risk and time to diagnosis (respectively), adjusting for other risk factors. Results: Among 154 newly diagnosed cases and 308 matched controls, RCC was associated with higher whole blood lead [OR = 2.0; 95% confidence interval (CI), 1.0–3.9; quartile 4 (Q4) vs. Q1, Ptrend = 0.022] and CALB1 rs1800645 (Ptrend = 0.025, minor ‘T' allele frequency = 0.34). Higher total serum calcium (Ptrend ≤ 0.001) was associated with reduced RCC risk. Total serum calcium and 25-hydroxyvitamin D levels did not alter the association observed with lead. Time from enrollment to RCC diagnosis was positively associated with serum calcium (Ptrend = 0.002) and 25-hydroxyvitamin D (Ptrend = 0.054) among cases. Conclusions: Higher blood lead concentrations, below the 10 μg/dL level of concern, were associated with RCC, independent from serum calcium and CALB1 promoter polymorphism. Impact: Increased risk of RCC is associated with lower serum calcium and higher whole blood lead in smokers. The clinical prognostic value of serum calcium and vitamin D in RCC should be further investigated. Cancer Epidemiol Biomarkers Prev; 21(1); 191–201. ©2011 AACR.
An examination of the organisational commitment of financial planners

This paper sets out to determine whether the demographic variables of age, gender, length of service can be shown to be related to the organisational commitment (OC) of financial planners in Australia. The financial planners were surveyed using an instrument derived from established questionnaires. It was mailed nationally to 312 financial planners. A response rate of 36% was achieved, equating to 113 useable responses. The analyses revealed statistically significant results at the 95% confidence level (p=0.05), that female respondents demonstrated a statistically significant higher level of OC than did their male counterparts.Such findings contribute to our understanding of the organisational commitment of Financial Planners, and have implications for employers in terms of hiring and retention of employees. The analyses are also important from a public policy perspective in an era of increasing attention given to, and likely increased regulation of, the financial planning industry.