Adaptive dual-comb spectroscopy in the green region

Dual-comb spectroscopy is extended to the visible spectral range with a set-up based on two frequency-doubled femtosecond ytterbium-doped fiber lasers. The dense rovibronic spectrum of iodine around 19240 cm-1 is recorded within 12 ms at Doppler-limited resolution with a simple scheme that only uses free-running femtosecond lasers

Raman-induced Kerr-effect dual-comb spectroscopy

We report on the first demonstration of nonlinear dual-frequency-comb spectroscopy. In multi-heterodyne femtosecond Raman-induced Kerr-effect spectroscopy, the Raman gain resulting from the coherent excitation of molecular vibrations by a spectrally-narrow pump is imprinted onto the femtosecond laser frequency comb probe spectrum. The birefringence signal induced by the nonlinear interaction of these beams and the sample is heterodyned against a frequency comb local oscillator with a repetition frequency slightly different from that of the comb probe. Such time-domain interference provides multiplex access to the phase and amplitude Raman spectra over a broad spectral bandwidth within a short measurement time. Experimental demonstration, at a spectral resolution of 200 GHz, a measurement time of 293 {\mu}s and a sensitivity of 10^-6, is given on liquid samples exhibiting a C-H stretch Raman shift.Comment: 7 pages, 4 figure

Biomarkers and neuromodulation techniques in substance use disorders

Addictive disorders are a severe health concern. Conventional therapies have just moderate success and the probability of relapse after treatment remains high. Brain stimulation techniques, such as transcranial Direct Current Stimulation (tDCS) and Deep Brain Stimulation (DBS), have been shown to be effective in reducing subjectively rated substance craving. However, there are few objective and measurable parameters that reflect neural mechanisms of addictive disorders and relapse. Key electrophysiological features that characterize substance related changes in neural processing are Event-Related Potentials (ERP). These high temporal resolution measurements of brain activity are able to identify neurocognitive correlates of addictive behaviours. Moreover, ERP have shown utility as biomarkers to predict treatment outcome and relapse probability. A future direction for the treatment of addiction might include neural interfaces able to detect addiction-related neurophysiological parameters and deploy neuromodulation adapted to the identified pathological features in a closed-loop fashion. Such systems may go beyond electrical recording and stimulation to employ sensing and neuromodulation in the pharmacological domain as well as advanced signal analysis and machine learning algorithms. In this review, we describe the state-of-the-art in the treatment of addictive disorders with electrical brain stimulation and its effect on addiction-related neurophysiological markers. We discuss advanced signal processing approaches and multi-modal neural interfaces as building blocks in future bioelectronics systems for treatment of addictive disorders

Domestic Outsourcing in the United States: A Research Agenda to Assess Trends and Effects on Job Quality

The goal of this paper is to develop a comprehensive research agenda to analyze trends in domestic outsourcing in the United States—firms’ use of contractors and independent contractors—and its effects on job quality and inequality. In the process, we review definitions of outsourcing, the available scant empirical research, and limitations of existing data sources. We also summarize theories that attempt to explain why firms contract out for certain functions and assess their predictions about likely impacts on job quality. We then lay out in detail a major research initiative on domestic outsourcing, discussing the questions it should answer and providing a menu of research methodologies and potential data sources. Such a research investment will be a critical resource for policymakers and other stakeholders as they seek solutions to problems arising from the changing nature of work

A meta-analysis on progressive atrophy in intractable temporal lobe epilepsy Time is brain?

Objective: It remains unclear whether drug-resistant temporal lobe epilepsy (TLE) is associated with cumulative brain damage, with no expert consensus and no quantitative syntheses of the available evidence. Methods: We conducted a systematic review and meta-analysis of MRI studies on progressive atrophy, searching PubMed and Ovid MEDLINE databases for cross-sectional and longitudinal quantitative MRI studies on drug-resistant TLE. Results: We screened 2,976 records and assessed eligibility of 248 full-text articles. Forty-two articles met the inclusion criteria for quantitative evaluation. We observed a predominance of cross-sectional studies, use of different clinical indices of progression, and high heterogeneity in age-control procedures. Meta-analysis of 18/1 cross-sectional/longitudinal studies on hippocampal atrophy (n 5 979 patients) yielded a pooled effect size of r 5 20.42 for ipsilateral atrophy related to epilepsy duration (95% confidence interval [CI] 20.51 to 20.32; p , 0.0001; I 2 5 65.22%) and r 5 20.35 related to seizure frequency (95% CI 20.47 to 20.22; p , 0.0001; I 2 5 61.97%). Sensitivity analyses did not change the results. Narrative synthesis of 25/3 crosssectional/longitudinal studies on whole brain atrophy (n 5 1,504 patients) indicated that .80% of articles reported duration-related progression in extratemporal cortical and subcortical regions. Detailed analysis of study design features yielded low to moderate levels of evidence for progressive atrophy across studies, mainly due to dominance of cross-sectional over longitudinal investigations, use of diverse measures of seizure estimates, and absence of consistent age control procedures. Conclusions: While the neuroimaging literature is overall suggestive of progressive atrophy in drug-resistant TLE, published studies have employed rather weak designs to directly demonstrate it. Longitudinal multicohort studies are needed to unequivocally differentiate aging from disease progression