Insomnia disorder is highly prevalent and frequently co-exists with other mental health conditions. Evidence suggests that targeting insomnia may improve overall mental health. Although the effectiveness of cognitive behavioural therapy for insomnia (CBT-I) is well established, it is rarely offered to patients as a discrete treatment. This study aimed to evaluate the outcomes of CBT-I delivered at Step 2 for reducing symptoms of insomnia, as well as anxiety, depression, and impaired functioning, following its implementation within an NHS Talking Therapies service. We examined routinely collected pre- and post-treatment outcomes from 35 patients (median age 60 years, interquartile range 44–68, 63% female) who received CBT-I. Insomnia severity was assessed during the first and last session using the Insomnia Severity Index, while secondary outcomes, including depression, anxiety, and impaired functioning were completed at each session. Intention-to-treat analyses demonstrated significant improvements in insomnia symptoms from pre- to post-treatment, with a large effect size (d = 0.85). Significant improvements were also observed across all secondary outcomes, with large effect sizes for depression (d = 1.01) and anxiety (d = 0.89), and a medium effect size for functioning (d = 0.58). The complete case analysis yielded larger effect sizes across most outcomes. These findings provide preliminary support for the potential benefits of CBT-I as a primary treatment for symptoms of insomnia, with secondary benefits for anxiety, depression, and functioning in patients presenting with mental health difficulties within an NHS Talking Therapies service. Implications for the service and future service evaluations are discussed.

Key learning aims

1. (1) To develop understanding of the evidence base for CBT-I for sleep and mental health outcomes.

2. (2) To consider the outcomes of CBT-I when delivered by Psychological Wellbeing Practitioners in an NHS Talking Therapies service.

3. (3) To evaluate clinical recovery rates in line with NHS Talking Therapies criteria.

The stars of the Milky Way carry the chemical history of our Galaxy in their atmospheres as they journey through its vast expanse. Like barcodes, we can extract the chemical fingerprints of stars from high-resolution spectroscopy. The fourth data release (DR4) of the Galactic Archaeology with HERMES (GALAH) Survey, based on a decade of observations, provides the chemical abundances of up to 32 elements for 917 588 stars that also have exquisite astrometric data from the Gaia satellite. For the first time, these elements include life-essential nitrogen to complement carbon, and oxygen as well as more measurements of rare-earth elements critical to modern-life electronics, offering unparalleled insights into the chemical composition of the Milky Way. For this release, we use neural networks to simultaneously fit stellar parameters and abundances across the whole wavelength range, leveraging synthetic grids computed with Spectroscopy Made Easy. These grids account for atomic line formation in non-local thermodynamic equilibrium for 14 elements. In a two-iteration process, we first fit stellar labels to all 1 085 520 spectra, then co-add repeated observations and refine these labels using astrometric data from Gaia and 2MASS photometry, improving the accuracy and precision of stellar parameters and abundances. Our validation thoroughly assesses the reliability of spectroscopic measurements and highlights key caveats. GALAH DR4 represents yet another milestone in Galactic archaeology, combining detailed chemical compositions from multiple nucleosynthetic channels with kinematic information and age estimates. The resulting dataset, covering nearly a million stars, opens new avenues for understanding not only the chemical and dynamical history of the Milky Way but also the broader questions of the origin of elements and the evolution of planets, stars, and galaxies.

The use of coffins and jars as funerary receptacles was common across Southeast Asia. During the fifteenth to seventeenth centuries AD, cremation was the dominant mortuary tradition on the Angkorian plains, but in the Cardamom Mountains to the south, contemporaneous groups practised a unique burial tradition involving the deposition of un-cremated bone in exposed ceramic vessels and log coffins. The authors present the first geochemical analysis of individuals from this highland culture, specifically the site of Phnom Pel. The childhood diets of those interred in jars and coffins may have been sourced from different areas within the Cardamom Mountains, suggesting that the individuals came from discrete groups.

Laser–solid interactions are highly suited as a potential source of high energy X-rays for nondestructive imaging. A bright, energetic X-ray pulse can be driven from a small source, making it ideal for high resolution X-ray radiography. By limiting the lateral dimensions of the target we are able to confine the region over which X-rays are produced, enabling imaging with enhanced resolution and contrast. Using constrained targets we demonstrate experimentally a $(20\pm 3)~\unicode[STIX]{x03BC}\text{m}$ X-ray source, improving the image quality compared to unconstrained foil targets. Modelling demonstrates that a larger sheath field envelope around the perimeter of the constrained targets increases the proportion of electron current that recirculates through the target, driving a brighter source of X-rays.

Relationships between snow structure, climatic factors, and the nature of avalanche events in the San Juan Mountains of Colorado, U.S.A., are analyzed. Physical and mechanical properties of the snow cover have been monitored on a continuous basis by conventional methods as well as through the application of a profiling snow-density gauge. Temperature-gradient metamorphism is the dominant mechanism which determines the character of the local snow structure. Properties unique to well-developed temperature-gradient snow (depth hoar) are discussed. Three specific metamorphic processes are described which contribute to a highly varied and mechanically weak snow structure. Analysis of fracture-line profile data allow general studies of the local snow climate to be compared with the stratigraphy of actual release zones. Fracture-line data support the conclusion that meteorological conditions prevailing at the time of new-snow deposition play a less significant role in the eventual release of slab avalanches than metamorphic processes which influence the snow cover between storm periods. Shear failure zones are consistently composed of weak layers metamorphosed weeks and even months prior to the precipitation event which triggers the release.

On 16–18 June 2008 the US National Snow and Ice Data Center held a GLIMS workshop in Boulder, CO, USA, focusing on formulating procedures and best practices for operational glacier mapping using satellite imagery. Despite the progress made in recent years, there still remain many cases where automatic delineation of glacier boundaries in satellite imagery is difficult, error prone or time-consuming. This workshop identified six themes for consideration by focus groups: (1) mapping clean ice and lakes; (2) mapping ice divides; (3) mapping debris-covered glaciers; (4) assessing changes in glacier area and elevation through comparisons with older data; (5) digital elevation model (DEM) generation from satellite stereo pairs; and (6) accuracy and error analysis. Talks presented examples and work in progress for each of these topics, and focus groups worked on compiling a summary of available algorithms and procedures to address and avoid identified hurdles. Special emphasis was given to establishing standard protocols for glacier delineation and analysis, creating illustrated tutorials and providing source code for available methods. This paper summarizes the major results of the 2008 GLIMS workshop, with an emphasis on definitions, methods and recommendations for satellite data processing. While the list of proposed methods and recommendations is not comprehensive and is still a work in progress, our goal here is to provide a starting point for the GLIMS regional centers as well as for the wider glaciological community in terms of documentation on possible pitfalls along with potential solutions.

Passive-microwave satellite remote sensing can greatly enhance large-scale snow measurements based on visible satellite data alone because of the ability to acquire data through most clouds or during darkness as well as to provide a measure of snow depth or water equivalent. This study provides preliminary results from the comparison and evaluation of several different passive-microwave algorithms. These algorithms represent examples which include both mid- and high-frequency channels, vertical and horizontal polarizations and polarization-difference approaches. In our comparisons we utilize larger, more comprehensive, validation datasets which can be expected to provide a full range of snow/climate conditions rather than limited data which may only represent a snapshot in time and space. Evaluation of snow extent derived from passive-microwave data is undertaken through comparison with the U.S. National Oceanic and Atmospheric Administration (NOAA) Northern Hemisphere snow charts which are based on visible-band satellite data. Results clearly indicate those time periods and geographic regions where the two techniques agree and where they tend to consistently disagree. Validation of snow water equivalent derived from passive-microwave data is undertaken using measurements from snow-course transects in the former Soviet Union. Preliminary results indicate a general tendency for nearly all of the algorithms to underestimate snow water equivalent.

In this study, we report on the spatial and temporal distribution of seasonal snow depth derived from passive microwave satellite remote-sensing data (e.g. SMMR from 1978 to 1987 and SMM/ I from 1987 to 2006) in China. We first modified the Chang algorithm and then validated it using meteorological observation data, considering the influences from vegetation, wet snow, precipitation, cold desert and frozen ground. Furthermore, the modified algorithm is dynamically adjusted based on the seasonal variation of grain size and snow density. Snow-depth distribution is indirectly validated by MODIS snow-cover products by comparing the snow-extent area from this work. The final snow-depth datasets from 1978 to 2006 show that the interannual snow-depth variation is very significant. The spatial and temporal distribution of snow depth is illustrated and discussed, including the steady snow-cover regions in China and snow-mass trend in these regions. Though the areal extent of seasonal snow cover in the Northern Hemisphere indicates a weak decrease over a long period, there is no clear trend in change of snow-cover area extent in China. However, snow mass over the Qinghai–Tibetan Plateau and northwestern China has increased, while it has weakly decreased in northeastern China. Overall, snow depth in China during the past three decades shows significant interannual variation, with a weak increasing trend.