SCREENING FOR A MULTIVARIATE MIXTURE NORMAL DISTRIBUTION

Abstract. The screening problem has been studied by many authors mostly focused on individual multivariate normal model with screening for normal distribution when all or part of the parameters are known, or the performance variable is dichotomous. In this paper a screening method is presented when the screening variable is a mixture of two multivariate normal distributions, meanwhile the performance variable is dichotomous. The method is used for the case when the parameters are known or estimated from separate samples. To reduce the dimensionality of the problem and therefore the scale of the computation, a Fisher's linear discrimination function is applied to find coefficients of a standard linear combination of the variables used in the proposed method. A comparison of methods is made for Conn's syndrome date. The results of the study are equivalent to the predictive screening approach

Overview of the 2023 ICASSP SP Clarity Challenge: Speech Enhancement for Hearing Aids

This paper reports on the design and outcomes of the ICASSP SP Clarity Challenge: Speech Enhancement for Hearing Aids. The scenario was a listener attending to a target speaker in a noisy, domestic environment. There were multiple interferers and head rotation by the listener. The challenge extended the second Clarity Enhancement Challenge (CEC2) by fixing the amplification stage of the hearing aid; evaluating with a combined metric for speech intelligibility and quality; and providing two evaluation sets, one based on simulation and the other on real-room measurements. Five teams improved on the baseline system for the simulated evaluation set, but the performance on the measured evaluation set was much poorer. Investigations are on-going to determine the exact cause of the mismatch between the simulated and measured data sets. The presence of transducer noise in the measurements, lower order Ambisonics harming the ability for systems to exploit binaural cues and the differences between real and simulated room impulse responses are suggested causes

Perception and automatic detection of wind-induced microphone noise

Wind can induce noise on microphones, causing problems for users of hearing aids and for those making recordings outdoors. Perceptual tests in the laboratory and via the Internet were carried out to understand what features of wind noise are important to the perceived audio quality of speech recordings. The average A-weighted sound pressure level of the wind noise was found to dominate the perceived degradation of quality, while gustiness was mostly unimportant. Large degradations in quality were observed when the signal to noise ratio was lower than about 15 09dB. A model to allow an estimation of wind noise level was developed using an ensemble of decision trees. The model was designed to work with a single microphone in the presence of a variety of foreground sounds. The model outputted four classes of wind noise: none, low, medium, and high. Wind free examples were accurately identified in 79% of cases. For the three classes with noise present, on average 93% of samples were correctly assigned. A second ensemble of decision trees was used to estimate the signal to noise ratio and thereby infer the perceived degradation caused by wind noise

The 2nd Clarity Prediction Challenge: A machine learning challenge for hearing aid intelligibility prediction

This paper reports on the design and outcomes of the 2nd Clarity Prediction Challenge (CPC2) for predicting the intelligibility of hearing aid processed signals heard by individuals with a hearing impairment. The challenge was designed to promote new approaches for estimating the intelligibility of hearing aid signals that can be used in future hearing aid algorithm development. It extends an earlier round (CPC1, 2022) in a number of critical directions, including a larger dataset coming from new speech intelligibility listening experiments, a greater degree of variability in the test materials, and a design that requires prediction systems to generalise to unseen algorithms and listeners. This paper provides a full description of the new publicly available CPC2 dataset, the CPC2 challenge design, and the baseline systems. The challenge attracted 12 systems from 9 research teams. The systems are reviewed, their performance is analysed and conclusions are presented, with reference to the progress made since the earlier CPC1 challenge. In particular, it is seen how reference-free, non-intrusive systems based on pre-trained large acoustic models can perform well in this context

Project Freebird: An orbital transfer vehicle

Freebird is a space-based orbital transfer vehicle designed to repair and deorbit orbital assets. Freebird is based at International Space Station Alpha (ISSA) at an inclination of 51.6 deg and is capable of three types of missions: crewed and teleoperated LEO missions, and extended robotic missions. In a crewed local configuration, the vehicle can visit inclinations between 30.8 deg and 72.4 deg at altitudes close to 390 km. Adding extra fuel tanks extends this range of inclination up to 84.9 deg and down to 18.3 deg. Furthermore, removing the crew module, using the vehicle in a teleoperated manner, and operating with extra fuel tanks allows missions to polar and geosynchronous orbits. To allow for mission flexibility, the vehicle was designed in a semimodular configuration. The major system components include a crew module, a 'smart box' (which contains command, communications, guidance, and navigation equipment), a propulsion pack, extra fuel tanks, and a vehicle storage facility (VSF) for storage purposes. To minimize risk as well as development time and cost, the vehicle was designed using only proven technology or technology which is expected to be flight-qualified in time for the intended launch date of 2002. And, because Freebird carries crew and operates near the space station, it must meet or exceed the NASA reliability standard of 0.994, as well as other standard requirements for such vehicles. The Freebird program was conceived and designed as a way to provide important and currently unavailable satellite repair and replacement services of a value equal to or exceeding operational costs

Signaling in Secret: Pay-for-Performance and the Incentive and Sorting Effects of Pay Secrecy

Key Findings: Pay secrecy adversely impacts individual task performance because it weakens the perception that an increase in performance will be accompanied by increase in pay; Pay secrecy is associated with a decrease in employee performance and retention in pay-for-performance systems, which measure performance using relative (i.e., peer-ranked) criteria rather than an absolute scale (see Figure 2 on page 5); High performing employees tend to be most sensitive to negative pay-for- performance perceptions; There are many signals embedded within HR policies and practices, which can influence employees’ perception of workplace uncertainty/inequity and impact their performance and turnover intentions; and When pay transparency is impractical, organizations may benefit from introducing partial pay openness to mitigate these effects on employee performance and retention

Antidepressant use and risk of epilepsy and seizures in people aged 20 to 64 years: cohort study using a primary care database

Background: Epilepsy is a serious condition which can profoundly affect an individual’s life. While there is some evidence to suggest an association between antidepressant use and epilepsy and seizures it is conflicting and not conclusive. Antidepressant prescribing is rising in the UK so it is important to quantify absolute risks with individual antidepressants to enable shared decision making with patients. In this study we assess and quantify the association between antidepressant treatment and the risk of epilepsy and seizures in a large cohort of patients diagnosed with depression aged between 20 and 64 years. Methods: Data on 238,963 patients with a diagnosis of depression aged 20 to 64 from 687 UK practices were extracted from the QResearch primary care database. We used Cox’s proportional hazards to analyse the time to the first recorded diagnosis of epilepsy/seizures, excluding patients with a prior history and estimated hazard ratios for antidepressant exposure adjusting for potential confounding variables. Results: In the first 5 years of follow-up, 878 (0.37 %) patients had a first diagnosis of epilepsy/seizures with the hazard ratio (HR) significantly increased (P < 0.01) for all antidepressant drug classes and for 8 of the 11 most commonly prescribed drugs. The highest risks (in the first 5 years) compared with no treatment were for trazodone (HR 5.41, 95 % confidence interval (CI) 3.05 to 9.61, number needed to harm (NNH) 65), lofepramine (HR 3.09, 95 % CI 1.73 to 5.50, NNH 138), venlafaxine (HR 2.84, 95 % CI 1.97 to 4.08, NNH 156) and combined antidepressant treatment (HR 2.73, 95 % CI 1.52 to 4.91, NNH 166). Conclusions: Risk of epilepsy/seizures is significantly increased for all classes of antidepressant. There is a need for individual risk-benefit assessments in patients being considered for antidepressant treatment, especially those with ongoing mild depression or with additional risk factors. Residual confounding and indication bias may influence our results, so confirmation may be required from additional studies

Genetic risk and a primary role for cell-mediated immune mechanisms in multiple sclerosis.

Multiple sclerosis is a common disease of the central nervous system in which the interplay between inflammatory and neurodegenerative processes typically results in intermittent neurological disturbance followed by progressive accumulation of disability. Epidemiological studies have shown that genetic factors are primarily responsible for the substantially increased frequency of the disease seen in the relatives of affected individuals, and systematic attempts to identify linkage in multiplex families have confirmed that variation within the major histocompatibility complex (MHC) exerts the greatest individual effect on risk. Modestly powered genome-wide association studies (GWAS) have enabled more than 20 additional risk loci to be identified and have shown that multiple variants exerting modest individual effects have a key role in disease susceptibility. Most of the genetic architecture underlying susceptibility to the disease remains to be defined and is anticipated to require the analysis of sample sizes that are beyond the numbers currently available to individual research groups. In a collaborative GWAS involving 9,772 cases of European descent collected by 23 research groups working in 15 different countries, we have replicated almost all of the previously suggested associations and identified at least a further 29 novel susceptibility loci. Within the MHC we have refined the identity of the HLA-DRB1 risk alleles and confirmed that variation in the HLA-A gene underlies the independent protective effect attributable to the class I region. Immunologically relevant genes are significantly overrepresented among those mapping close to the identified loci and particularly implicate T-helper-cell differentiation in the pathogenesis of multiple sclerosis

The impact of diabetes mellitus on survival following resection and adjuvant chemotherapy for pancreatic cancer

BACKGROUND: Diabetes mellitus is frequently observed in pancreatic cancer patients and is both a risk factor and an early manifestation of the disease. METHODS: We analysed the prognostic impact of diabetes on the outcome of pancreatic cancer following resection and adjuvant chemotherapy using individual patient data from three European Study Group for Pancreatic Cancer randomised controlled trials. Analyses were carried out to assess the association between clinical characteristics and the presence of preoperative diabetes, as well as the effect of diabetic status on overall survival. RESULTS: In total, 1105 patients were included in the analysis, of whom 257 (23%) had confirmed diabetes and 848 (77%) did not. Median (95% confidence interval (CI)) unadjusted overall survival in non-diabetic patients was 22.3 (20.8–24.1) months compared with 18.8 (16.9–22.1) months for diabetic patients (P=0.24). Diabetic patients were older, had increased weight and more co-morbidities. Following adjustment, multivariable analysis demonstrated that diabetic patients had an increased risk of death (hazard ratio: 1.19 (95% CI 1.01, 1.40), P=0.034). Maximum tumour size of diabetic patients was larger at randomisation (33.6 vs 29.7 mm, P=0.026). CONCLUSIONS: Diabetes mellitus was associated with increased tumour size and reduced survival following pancreatic cancer resection and adjuvant chemotherapy