Optical-parametric-amplification-enhanced background-free spectroscopy.

Traditional absorption spectroscopy has a fundamental difficulty in resolving small absorbance from a strong background due to the instability of laser sources. Existing background-free methods in broadband vibrational spectroscopy help to alleviate this problem but face challenges in realizing either low extinction ratios or time-resolved field measurements. Here, we introduce optical-parametric-amplification-enhanced background-free spectroscopy, in which the excitation background is first suppressed by an interferometer, and then the free-induction decay that carries molecular signatures is selectively amplified. We show that this method can improve the limit of detection in linear interferometry by order(s) of magnitude without requiring lower extinction ratios or a time-resolved measurement, which can benefit sensing applications in detecting trace species.

Management of a Trichophyton tonsurans outbreak in a day-care center.

Trichophyton tonsurans is the leading cause of tinea capitis in the United Kingdom (UK) as well as causing tinea corporis. This organism has been linked to several outbreaks in the UK and abroad, and such outbreaks may be prolonged since T. tonsurans can be difficult to control. There remains an incomplete consensus in the literature on the optimal management of such outbreaks of this infection. Following notification that a child with T. tonsurans was identified at a day-care center in the UK, initial investigations identified nine cases of fungal infection involving children and staff over the previous 7 months. We report on the management of an outbreak of T. tonsurans tinea capitis and tinea corporis among children and staff in a day-care center. An outbreak control team with representatives from dermatology, microbiology, day-care center management, and the Health Protection Agency initiated case ascertainment by scalp inspection and brushing of all children and staff at the nursery. Two complete rounds of screening were required before the outbreak was declared over. Infection control measures included antifungal shampoo use, exclusion of identified cases for a short period, removal of shared items from the center, and enhanced decontamination of fomites. The outbreak, which lasted longer than 12 months, involved 12 children and 7 staff members. Of these, 12 cases were confirmed by positive fungal culture. T. tonsurans is difficult to manage, especially in childcare settings, but case ascertainment, appropriate treatment with oral agents, and sustained infection control measures can be effective in controlling such outbreaks.

Mid-infrared cross-comb spectroscopy.

Dual-comb spectroscopy has been proven beneficial in molecular characterization but remains challenging in the mid-infrared region due to difficulties in sources and efficient photodetection. Here we introduce cross-comb spectroscopy, in which a mid-infrared comb is upconverted via sum-frequency generation with a near-infrared comb of a shifted repetition rate and then interfered with a spectral extension of the near-infrared comb. We measure CO2 absorption around 4.25 µm with a 1-µm photodetector, exhibiting a 233-cm-1 instantaneous bandwidth, 28000 comb lines, a single-shot signal-to-noise ratio of 167 and a figure of merit of 2.4 × 106 Hz1/2. We show that cross-comb spectroscopy can have superior signal-to-noise ratio, sensitivity, dynamic range, and detection efficiency compared to other dual-comb-based methods and mitigate the limits of the excitation background and detector saturation. This approach offers an adaptable and powerful spectroscopic method outside the well-developed near-IR region and opens new avenues to high-performance frequency-comb-based sensing with wavelength flexibility.

Empirical use of temocillin in hospitalized patients: results from a retrospective audit.

Background: Following a global shortage of piperacillin/tazobactam in 2017, a formulary decision was taken at a large District General Hospital in the East of England to partly replace piperacillin/tazobactam with either temocillin as monotherapy or as part of a combination regimen. A retrospective audit was then conducted to assess the clinical effectiveness of temocillin therapy. Methods: Data from patients admitted to Watford General Hospital between May and August 2017 and treated with temocillin were reviewed retrospectively. Clinical characteristics of patients, data related to the episode of infection, clinical success, tolerance and mortality were analysed. Results: Temocillin was used in 126 patients with median age of 73 years. Infection episodes mostly originated from the abdomen (n = 46), the lung (n = 40) and the urinary tract (n = 21). Seventy-seven patients received temocillin as first-line therapy and 106 received it empirically, with temocillin prescribed in combination with another antibiotic in 82% of the empirically treated cases. Clinical success was observed in 88.9% of cases with no difference between patients treated empirically and others (89.6% versus 85%) or in efficacy among abdominal (91%), pulmonary (87.5%) and urinary (81%) infections. One case of Clostridioides difficile infection was reported in a patient treated with four different antibiotics. During the shortage period, the hospital's standardized mortality ratio was significantly lower when compared with the same period of the preceding year (85 versus 96). Conclusions: Using temocillin as part of an empirical strategy is feasible and safe as long as appropriate antibiotic combination is recommended based upon the indication and the likely bacterial pathogen.

Ultrafast mode-locked laser in nanophotonic lithium niobate.

Mode-locked lasers (MLLs) generate ultrashort pulses with peak powers substantially exceeding their average powers. However, integrated MLLs that drive ultrafast nanophotonic circuits have remained elusive because of their typically low peak powers, lack of controllability, and challenges when integrating with nanophotonic platforms. In this work, we demonstrate an electrically pumped actively MLL in nanophotonic lithium niobate based on its hybrid integration with a III-V semiconductor optical amplifier. Our MLL generates [Formula: see text]4.8-ps optical pulses around 1065 nm at a repetition rate of ∼10 GHz, with energies exceeding 2.6 pJ and peak powers beyond 0.5 W. The repetition rate and the carrier-envelope offset frequency of the output can be controlled in a wide range by using the driving frequency and the pump current, providing a route for fully stabilized on-chip frequency combs.

Few-cycle vacuum squeezing in nanophotonics.

One of the most fundamental quantum states of light is the squeezed vacuum, in which noise in one of the quadratures is less than the standard quantum noise limit. In nanophotonics, it remains challenging to generate, manipulate, and measure such a quantum state with the performance required for a wide range of scalable quantum information systems. Here, we report the development of a lithium niobate-based nanophotonic platform to demonstrate the generation and all-optical measurement of squeezed states on the same chip. The generated squeezed states span more than 25 terahertz of bandwidth supporting just a few optical cycles. The measured 4.9 decibels of squeezing surpass the requirements for a wide range of quantum information systems, demonstrating a practical path toward scalable ultrafast quantum nanophotonics.

A robust hidden Markov Gauss mixture vector quantizer for a noisy source.

Noise is ubiquitous in real life and changes image acquisition, communication, and processing characteristics in an uncontrolled manner. Gaussian noise and Salt and Pepper noise, in particular, are prevalent in noisy communication channels, camera and scanner sensors, and medical MRI images. It is not unusual for highly sophisticated image processing algorithms developed for clean images to malfunction when used on noisy images. For example, hidden Markov Gauss mixture models (HMGMM) have been shown to perform well in image segmentation applications, but they are quite sensitive to image noise. We propose a modified HMGMM procedure specifically designed to improve performance in the presence of noise. The key feature of the proposed procedure is the adjustment of covariance matrices in Gauss mixture vector quantizer codebooks to minimize an overall minimum discrimination information distortion (MDI). In adjusting covariance matrices, we expand or shrink their elements based on the noisy image. While most results reported in the literature assume a particular noise type, we propose a framework without assuming particular noise characteristics. Without denoising the corrupted source, we apply our method directly to the segmentation of noisy sources. We apply the proposed procedure to the segmentation of aerial images with Salt and Pepper noise and with independent Gaussian noise, and we compare our results with those of the median filter restoration method and the blind deconvolution-based method, respectively. We show that our procedure has better performance than image restoration-based techniques and closely matches to the performance of HMGMM for clean images in terms of both visual segmentation results and error rate.

Prevalence of aggressive behaviour after severe paediatric traumatic brain injury.

OBJECTIVE: The goals of this study were to explore the prevalence of aggressive behaviours after severe paediatric traumatic brain injury (TBI) and identify predictors of aggressive behaviours 1 year post-injury. METHODS: A cohort of 97 children aged 4-19 years at time of severe TBI (GCS 3-8) were prospectively followed for 1 year. Pre-injury psychiatric status was obtained retrospectively at enrolment and post-injury behavioural and functional concerns were assessed at 1 year. Aggression was measured with a modified version of the Overt Aggression Scale (OAS). RESULTS: Results revealed aggressive behaviour increased from pre-injury to post-injury. Pre-injury factors including aggression, attention problems and anxiety were associated with increased post-injury aggressive behaviour. Children with greater disability after injury were also at increased risk for aggressive behaviours. CONCLUSIONS: Aggression is a prevalent symptom after paediatric TBI and can significantly impede rehabilitation. Awareness of these predictors can aid in early identification of children at risk in order to help appropriately design rehabilitation programmes.

Image segmentation using hidden Markov Gauss mixture models.

Image segmentation is an important tool in image processing and can serve as an efficient front end to sophisticated algorithms and thereby simplify subsequent processing. We develop a multiclass image segmentation method using hidden Markov Gauss mixture models (HMGMMs) and provide examples of segmentation of aerial images and textures. HMGMMs incorporate supervised learning, fitting the observation probability distribution given each class by a Gauss mixture estimated using vector quantization with a minimum discrimination information (MDI) distortion. We formulate the image segmentation problem using a maximum a posteriori criteria and find the hidden states that maximize the posterior density given the observation. We estimate both the hidden Markov parameter and hidden states using a stochastic expectation-maximization algorithm. Our results demonstrate that HMGMM provides better classification in terms of Bayes risk and spatial homogeneity of the classified objects than do several popular methods, including classification and regression trees, learning vector quantization, causal hidden Markov models (HMMs), and multiresolution HMMs. The computational load of HMGMM is similar to that of the causal HMM.

E-learning for medical imaging specialists: introducing blended learning in a nuclear medicine specialist course.

BACKGROUND: While e-learning has become an important tool in teaching medical students, the training of specialists in medical imaging is still dominated by lecture-based courses. PURPOSE: To assess the potential of e-learning in specialist education in medical imaging. MATERIAL AND METHODS: An existing lecture-based five-day course in Clinical Nuclear Medicine (NM) was enhanced by e-learning resources and activities, including practical exercises. An anonymized survey was conducted after participants had completed and passed the multiple choice electronic course examination. RESULTS: Twelve out of 15 course participants (80%) responded. Overall satisfaction with the new course format was high, but 25% of the respondents wanted more interactive elements such as discussions and practical exercises. The importance of lecture handouts and supplementary online material such as selected original articles and professional guidelines was affirmed by all the respondents (92% fully, 8% partially), while 75% fully and 25% partially agreed that the lectures had been interesting and relevant. CONCLUSION: E-learning represents a hitherto unrealized potential in the education of medical specialists. It may expedite training of medical specialists while at the same time containing costs.

Nonparametric supervised learning by linear interpolation with maximum entropy.

Nonparametric neighborhood methods for learning entail estimation of class conditional probabilities based on relative frequencies of samples that are "near-neighbors" of a test point. We propose and explore the behavior of a learning algorithm that uses linear interpolation and the principle of maximum entropy (LIME). We consider some theoretical properties of the LIME algorithm: LIME weights have exponential form; the estimates are consistent; and the estimates are robust to additive noise. In relation to bias reduction, we show that near-neighbors contain a test point in their convex hull asymptotically. The common linear interpolation solution used for regression on grids or look-up-tables is shown to solve a related maximum entropy problem. LIME simulation results support use of the method, and performance on a pipeline integrity classification problem demonstrates that the proposed algorithm has practical value.

Multivariate analyses of the profile stability of intelligence tests: high for IQs, low to very low for subtest analyses.

Profile stability involves the consistency of a set of scores over time. That is, does a profile of scores change on retesting and does this change affect clinical decisions? While psychologists routinely examine the reliability of individual scores, little research has examined the stability of a profile or set of scores. The first study described in this paper examined potential measures of profile stability using a simulation computer program. The results suggest that several measures show promise in this context, particularly Cattell's coefficient of pattern similarity (r(p)), salient variable similarity index (S), and the D(2) coefficient. In the second study, selected measures of profile stability were applied to Wechsler test-retest data. The results suggest that profiles composed of IQ and index scores demonstrate acceptable stability and can be usefully interpreted in clinical and research situations. However, subtest score profiles are inherently less stable and provide little useful clinical information.

Two sets of twins with selective mutism: neuropsychological findings.

Neuropsychological data are reviewed from two sets of dizygotic twins presenting with selective mutism characterized by situation specific anxiety, extreme passive behavior, lack of responsivity, lack of peer interaction, and a chronic course of selective mutism. Both sets of twins had a history of prematurity and delayed speech development. One set of twins presented with normal intelligence and normal receptive language skills but with expressive language and oral motor sequencing difficulties. The second set of twins presented with Verbal IQ deficits and significant receptive and expressive language deficits. A summary of current conceptualizations regarding etiology and treatment of selective mutism is provided.

Autistic-spectrum disorders in Down syndrome: further delineation and distinction from other behavioral abnormalities.

The present study extends our previous work characterizing the behavioral features of autistic-spectrum disorder (ASD) in Down syndrome (DS) using the Aberrant Behavior Checklist (ABC) and Autism Behavior Checklist (AutBehav). We examined which specific behaviors distinguished the behavioral phenotype of DS + ASD from other aberrant behavior disorders in DS, by determining the relative contribution of ABC and AutBehav subscales and items to the diagnosis of ASD. A total of 127 subjects (aged 2-24 years; mean age: 8.4 years; approximately 70% male), comprising: a cohort of 64 children and adolescents with DS and co-morbid ASD (DS + ASD), 19 with DS and stereotypic movement disorder (DS + SMD), 18 with DS and disruptive behaviors (DS + DB), and 26 with DS and no co-morbid behavior disorders (DS + none) were examined using the aforementioned measures of aberrant behavior. We found that subjects with DS + ASD showed the most severe aberrant behavior, especially stereotypy compared to DS + none and lethargy/social withdrawal and relating problems compared to DS + SMD. Specifically, relatively simple stereotypic behavior differentiated DS + ASD from DS + DB, whereas odd/bizarre stereotypic and anxious behavior characterized DS + ASD relative to DS + SMD and DS + none. Additionally, in a subset of subjects with DS + ASD and anxiety, social withdrawal was particularly pronounced. Overall, our findings indicate that a diagnosis of DS + ASD represents a distinctive set of aberrant behaviors marked by characteristic odd/bizarre stereotypic behavior, anxiety, and social withdrawal.

Autism spectrum disorder in Fragile X syndrome: differential contribution of adaptive socialization and social withdrawal.

The present study extends our previous work on characterizing the profile of social behavior abnormalities in boys with Fragile X (FraX) and autism spectrum disorder (ASD) using clinically oriented behavioral rating scales and standardized instruments. The goal was to further distinguish behavioral parameters contributing to the diagnostic classification of FraX + ASD. The study design included two cohorts of boys with FraX (3-8 years), a larger main cohort for cross-sectional analyses (n = 56, 24 with ASD), and a longitudinal subset (n = 30, 11 with ASD) of the main cohort with up to 3 yearly observations. The focus was on the relative contribution of delayed adaptive socialization and social withdrawal, including item components of their corresponding rating instruments, to the diagnosis of ASD in boys with FraX. Using a combination of regression analyses, we demonstrated that: (1) as delayed socialization, social withdrawal is also a correlate of FraX + ASD; (2) items of social withdrawal scales representing avoidance were the main predictors of ASD status, particularly in older boys; (3) adaptive socialization skills reflecting rules of social behavior and recognition and labeling of emotions, linked to verbal reasoning abilities, were selectively associated with FraX + ASD; (4) adaptive socialization is the primary determinant over time of ASD status in boys with FraX; and (5) integrated adaptive socialization-social withdrawal models allow the identification of distinctive FraX + ASD subgroups. Altogether, our findings suggest that two distinct but interrelated social behavior abnormalities, one linked to impaired cognitive processes (delayed socialization) and the second one to disturbance in limbic circuits (avoidance), play a role in the development of ASD in boys with FraX.

Autism spectrum disorder in fragile X syndrome: communication, social interaction, and specific behaviors.

The present study extends our previous work on social behavior impairment in young males with fragile X syndrome (FraX). Specifically, we evaluated whether the autistic phenomenon in FraX is expressed as a range of behavioral impairments as in idiopathic autism (Aut). We also examined whether there are behaviors, identified as items of the Autism Diagnostic Interview-Revised (ADI-R), that in FraX predispose to or differentiate subjects with autism spectrum disorder (ASD) diagnosis. Finally, regression models were utilized to test the relative contribution of reduced communication and socialization skills to ADI-R scores and diagnoses. A cohort of 56 boys (3-8 years) with FraX was examined in terms of scores on measures of cognition (IQ was a co-variate in most analyses.), autistic behavior, problem/aberrant behavior, adaptive behavior, and language development. We found that, indeed, in terms of problem behavior and adaptive skills, there is a range of severity from FraX + Aut to FraX + PDD (Pervasive Developmental Disorder) to FraX + none. ADI-R items representing "Play" types of interaction appear to be "susceptibility" factors since they were abnormal across the FraX cohort. Integrated regression models demonstrated that items reflecting complex social interaction differentiated the FraX + ASD (Aut + PDD) subgroup from the rest of the FraX cohort, while abnormalities in basic verbal and non-verbal communication distinguished the most severely affected boys with FraX + Aut from the milder FraX + PDD cohort. Models incorporating language, adaptive communication, and adaptive socialization skills revealed that socialization was not only the main influence on scores but also a predictor of ASD diagnosis. Altogether, our findings demonstrate that the diagnosis of ASD in FraX reflects, to a large extent, an impairment in social interaction that is expressed with variable severity in young males with FraX.