Ion Beam Sputtering Yield Measurements by Quartz Crystal Microbalance

Quartz-crystal microbalance (QCM) has been used as a sensitive device for the measurement of small mass changes for a long ago. In fact, using QCM we can measure the differential sputtering yield profile of a material, over a hemisphere above the target, very precisely. The sputtering yield depends on properties of both the incident ions (energy, mass, and incidence angle) and the target (mass, surface binding energy, surface topography, and even the crystal orientation). In our present study, we used a highly sensitive QCM to detect the mass change of the electrode material (gold and silver) through oscillations and calculated the corresponding sputtering yields. We used two types of ions, e.g, He and Ar, in an Ultra High Vacuum (UHV) chamber using the NTI ion gun as the ion source. Our experimental observation shows significantly higher sputtering yield values than that of the theoretically calculated ones, using SRIM simulations. In addition, we observed a significant reduction in the sputtering yield values with time, for a constant ion energy bombardment. Similarly, atomic force microscopy (AFM) study shows a significant reduction in the surface roughness values for a longer period of ion bombardment. These observations suggest that surface topography affects significantly the sputtering yield values. In the presentation the details of the disparities between experimental and the modeling will be discussed

The Role of Surface Roughness on Ion Sputtering Yield Measurements

Ion sputtering is the removal of surface atoms or molecules in a solid under energetic ion irradiation. This technique is promising for its applications in material modification and characterization. Sputtering yield, the average number of atoms removed from a sample per incident ion, is a crucial parameter in material modification. In the present study, a quartz crystal microbalance was used within an ultra-high vacuum chamber (10E-8 torr) to measure the sputtering yield of gold. An NTI-1401 ion gun was used to bombard argon and helium ions onto a gold sample. The argon and helium ions used ranged in energy from 100 – 5000 eV. Theoretical sputtering yield values were determined through simulation with Stopping and Range of Ions in Matter (SRIM) software and compared with experimentally measured values. The experimental values show a significantly higher sputtering yield for gold than that of the SRIM values; however they followed the same trend. Another observation was that for a constant ion energy bombardment the sputtering yield decreased with time. An atomic force microscopy (AFM) was performed before and after sputtering. The AFM showed that the surface of the sample became smoother after a period of ion bombardment. These observations suggest that surface topography significantly affects the sputtering yield values. The reasoning behind the discrepancy between experimental and SRIM sputtering yield values will be discussed

Why is it difficult to implement e-health initiatives? A qualitative study

<b>Background</b> The use of information and communication technologies in healthcare is seen as essential for high quality and cost-effective healthcare. However, implementation of e-health initiatives has often been problematic, with many failing to demonstrate predicted benefits. This study aimed to explore and understand the experiences of implementers - the senior managers and other staff charged with implementing e-health initiatives and their assessment of factors which promote or inhibit the successful implementation, embedding, and integration of e-health initiatives.<p></p> <b>Methods</b> We used a case study methodology, using semi-structured interviews with implementers for data collection. Case studies were selected to provide a range of healthcare contexts (primary, secondary, community care), e-health initiatives, and degrees of normalization. The initiatives studied were Picture Archiving and Communication System (PACS) in secondary care, a Community Nurse Information System (CNIS) in community care, and Choose and Book (C&B) across the primary-secondary care interface. Implementers were selected to provide a range of seniority, including chief executive officers, middle managers, and staff with 'on the ground' experience. Interview data were analyzed using a framework derived from Normalization Process Theory (NPT).<p></p> <b>Results</b> Twenty-three interviews were completed across the three case studies. There were wide differences in experiences of implementation and embedding across these case studies; these differences were well explained by collective action components of NPT. New technology was most likely to 'normalize' where implementers perceived that it had a positive impact on interactions between professionals and patients and between different professional groups, and fit well with the organisational goals and skill sets of existing staff. However, where implementers perceived problems in one or more of these areas, they also perceived a lower level of normalization.<p></p> <b>Conclusions</b> Implementers had rich understandings of barriers and facilitators to successful implementation of e-health initiatives, and their views should continue to be sought in future research. NPT can be used to explain observed variations in implementation processes, and may be useful in drawing planners' attention to potential problems with a view to addressing them during implementation planning

Reinforcement learning or active inference?

This paper questions the need for reinforcement learning or control theory when optimising behaviour. We show that it is fairly simple to teach an agent complicated and adaptive behaviours using a free-energy formulation of perception. In this formulation, agents adjust their internal states and sampling of the environment to minimize their free-energy. Such agents learn causal structure in the environment and sample it in an adaptive and self-supervised fashion. This results in behavioural policies that reproduce those optimised by reinforcement learning and dynamic programming. Critically, we do not need to invoke the notion of reward, value or utility. We illustrate these points by solving a benchmark problem in dynamic programming; namely the mountain-car problem, using active perception or inference under the free-energy principle. The ensuing proof-of-concept may be important because the free-energy formulation furnishes a unified account of both action and perception and may speak to a reappraisal of the role of dopamine in the brain

An increase in dietary n-3 fatty acids decreases a marker of bone resorption in humans

Human, animal, and in vitro research indicates a beneficial effect of appropriate amounts of omega-3 (n-3) polyunsaturated fatty acids (PUFA) on bone health. This is the first controlled feeding study in humans to evaluate the effect of dietary plant-derived n-3 PUFA on bone turnover, assessed by serum concentrations of N-telopeptides (NTx) and bone-specific alkaline phosphatase (BSAP). Subjects (n = 23) consumed each diet for 6 weeks in a randomized, 3-period crossover design: 1) Average American Diet (AAD; [34% total fat, 13% saturated fatty acids (SFA), 13% monounsaturated fatty acids (MUFA), 9% PUFA (7.7% LA, 0.8% ALA)]), 2) Linoleic Acid Diet (LA; [37% total fat, 9% SFA, 12% MUFA, 16% PUFA (12.6% LA, 3.6% ALA)]), and 3) α-Linolenic Acid Diet (ALA; [38% total fat, 8% SFA, 12% MUFA, 17% PUFA (10.5% LA, 6.5% ALA)]). Walnuts and flaxseed oil were the predominant sources of ALA. NTx levels were significantly lower following the ALA diet (13.20 ± 1.21 nM BCE), relative to the AAD (15.59 ± 1.21 nM BCE) (p < 0.05). Mean NTx level following the LA diet was 13.80 ± 1.21 nM BCE. There was no change in levels of BSAP across the three diets. Concentrations of NTx were positively correlated with the pro-inflammatory cytokine TNFα for all three diets. The results indicate that plant sources of dietary n-3 PUFA may have a protective effect on bone metabolism via a decrease in bone resorption in the presence of consistent levels of bone formation

Maternal obesity support services: a qualitative study of the perspectives of women and midwives

Background - Twenty percent of pregnant women in the UK are obese (BMI ≥ 30 kg/m2), reflecting the growing public health challenge of obesity in the 21st century. Obesity increases the risk of adverse outcomes during pregnancy and birth and has significant cost implications for maternity services. Gestational weight management strategies are a high priority; however the evidence for effective, feasible and acceptable weight control interventions is limited and inconclusive. This qualitative study explored the experiences and perceptions of pregnant women and midwives regarding existing support for weight management in pregnancy and their ideas for service development. Methods - A purposive sample of 6 women and 7 midwives from Doncaster, UK, participated in two separate focus groups. Transcripts were analysed thematically. Results - Two overarching themes were identified, 'Explanations for obesity and weight management' and 'Best care for pregnant women'. 'Explanations' included a lack of knowledge about weight, diet and exercise during pregnancy; self-talk messages which excused overeating; difficulties maintaining motivation for a healthy lifestyle; the importance of social support; stigmatisation; and sensitivity surrounding communication about obesity between midwives and their clients. 'Best care' suggested that weight management required care which was consistent and continuous, supportive and non-judgemental, and which created opportunities for interaction and mutual support between obese pregnant women. Conclusions - Women need unambiguous advice regarding healthy lifestyles, diet and exercise in pregnancy to address a lack of knowledge and a tendency towards unhelpful self-talk messages. Midwives expressed difficulties in communicating with their clients about their weight, given awareness that obesity is a sensitive and potentially stigmatising issue. This indicates more could be done to educate and support them in their work with obese pregnant women. Motivation and social support were strong explanatory themes for obesity and weight management, suggesting that interventions should focus on motivational strategies and social support facilitation

Active Nuclear Receptors Exhibit Highly Correlated AF-2 Domain Motions

Nuclear receptor ligand binding domains (LBDs) convert ligand binding events into changes in gene expression by recruiting transcriptional coregulators to a conserved activation function-2 (AF-2) surface. While most nuclear receptor LBDs form homo- or heterodimers, the human nuclear receptor pregnane X receptor (PXR) forms a unique and essential homodimer and is proposed to assemble into a functional heterotetramer with the retinoid X receptor (RXR). How the homodimer interface, which is located 30 Å from the AF-2, would affect function at this critical surface has remained unclear. By using 20- to 30-ns molecular dynamics simulations on PXR in various oligomerization states, we observed a remarkably high degree of correlated motion in the PXR–RXR heterotetramer, most notably in the four helices that create the AF-2 domain. The function of such correlation may be to create “active-capable” receptor complexes that are ready to bind to transcriptional coactivators. Indeed, we found in additional simulations that active-capable receptor complexes involving other orphan or steroid nuclear receptors also exhibit highly correlated AF-2 domain motions. We further propose a mechanism for the transmission of long-range motions through the nuclear receptor LBD to the AF-2 surface. Taken together, our findings indicate that long-range motions within the LBD scaffold are critical to nuclear receptor function by promoting a mobile AF-2 state ready to bind coactivators

Transcriptomic landscape of breast cancers through mRNA sequencing

Breast cancer is a heterogeneous disease with a poorly defined genetic landscape, which poses a major challenge in diagnosis and treatment. By massively parallel mRNA sequencing, we obtained 1.2 billion reads from 17 individual human tissues belonging to TNBC, Non-TNBC, and HER2-positive breast cancers and defined their comprehensive digital transcriptome for the first time. Surprisingly, we identified a high number of novel and unannotated transcripts, revealing the global breast cancer transcriptomic adaptations. Comparative transcriptomic analyses elucidated differentially expressed transcripts between the three breast cancer groups, identifying several new modulators of breast cancer. Our study also identified common transcriptional regulatory elements, such as highly abundant primary transcripts, including osteonectin, RACK1, calnexin, calreticulin, FTL, and B2M, and “genomic hotspots” enriched in primary transcripts between the three groups. Thus, our study opens previously unexplored niches that could enable a better understanding of the disease and the development of potential intervention strategies