Evaluation of UK Integrated Care Pilots: research protocol

<span style="font-family: Arial; mso-bidi-font-size: 11.0pt;"><span style="font-size: small;"><p align="left"><strong>Background</strong>: In response to concerns that the needs of the aging population for well-integrated care were increasing, the English National Health Service (NHS) appointed 16 Integrated Care Pilots following a national competition. The pilots have a range of aims including development of new organisational structures to support integration, changes in staff roles, reducing unscheduled emergency hospital admissions, reduced length of hospital stay, increasing patient satisfaction, and reducing cost. This paper describes the evaluation of the initiative which has been commissioned.</p><p align="justify"><strong>Study design and data collection methods</strong>: A mixed methods approach has been adopted including interviews with staff and patients, non-participant observation of meetings, structured written feedback from sites, questionnaires to patients and staff, and analysis of routinely collected hospital utilisation data for patients/service users. The qualitative analysis aims to identify the approaches taken to integration by the sites, the benefits which result, the context in which benefits have resulted, and the mechanisms by which they occur.</p><p align="justify"><strong>Methods of analysis</strong>: The quantitative analysis adopts a 'difference in differences' approach comparing health care utilisation before and after the intervention with risk-matched controls. The qualitative data analysis adopts a 'theory of change' approach in which we triangulate data from the quantitative analysis with qualitative data in order to describe causal effects (what happens when an independent variable changes) and causal mechanisms (what connects causes to their effects). An economic analysis will identify what incremental resources are required to make integration succeed and how they can be combined efficiently to produce better outcomes for patients.</p><p><strong>Conclusion</strong>: This evaluation will produce a portfolio of evidence aimed at strengthening the evidence base for integrated care, and in particular identifying the context in which interventions are likely to be effective. These data will support a series of evaluation judgements aimed at reducing uncertainties about the role of integrated care in improving the efficient and effective delivery of healthcare.</p></span></span

Public acceptability of government intervention to change health-related behaviours: a systematic review and narrative synthesis.

BACKGROUND: Governments can intervene to change health-related behaviours using various measures but are sensitive to public attitudes towards such interventions. This review describes public attitudes towards a range of policy interventions aimed at changing tobacco and alcohol use, diet, and physical activity, and the extent to which these attitudes vary with characteristics of (a) the targeted behaviour (b) the intervention and (c) the respondents. METHODS: We searched electronic databases and conducted a narrative synthesis of empirical studies that reported public attitudes in Europe, North America, Australia and New Zealand towards interventions relating to tobacco, alcohol, diet and physical activity. Two hundred studies met the inclusion criteria. RESULTS: Over half the studies (105/200, 53%) were conducted in North America, with the most common interventions relating to tobacco control (110/200, 55%), followed by alcohol (42/200, 21%), diet-related interventions (18/200, 9%), interventions targeting both diet and physical activity (18/200, 9%), and physical activity alone (3/200, 2%). Most studies used survey-based methods (160/200, 80%), and only ten used experimental designs. Acceptability varied as a function of: (a) the targeted behaviour, with more support observed for smoking-related interventions; (b) the type of intervention, with less intrusive interventions, those already implemented, and those targeting children and young people attracting most support; and (c) the characteristics of respondents, with support being highest in those not engaging in the targeted behaviour, and with women and older respondents being more likely to endorse more restrictive measures. CONCLUSIONS: Public acceptability of government interventions to change behaviour is greatest for the least intrusive interventions, which are often the least effective, and for interventions targeting the behaviour of others, rather than the respondent him or herself. Experimental studies are needed to assess how the presentation of the problem and the benefits of intervention might increase acceptability for those interventions which are more effective but currently less acceptable

Adversarial Defense by Restricting the Hidden Space of Deep Neural Networks

Deep neural networks are vulnerable to adversarial attacks, which can fool them by adding minuscule perturbations to the input images. The robustness of existing defenses suffers greatly under white-box attack settings, where an adversary has full knowledge about the network and can iterate several times to find strong perturbations. We observe that the main reason for the existence of such perturbations is the close proximity of different class samples in the learned feature space. This allows model decisions to be totally changed by adding an imperceptible perturbation in the inputs. To counter this, we propose to class-wise disentangle the intermediate feature representations of deep networks. Specifically, we force the features for each class to lie inside a convex polytope that is maximally separated from the polytopes of other classes. In this manner, the network is forced to learn distinct and distant decision regions for each class. We observe that this simple constraint on the features greatly enhances the robustness of learned models, even against the strongest white-box attacks, without degrading the classification performance on clean images. We report extensive evaluations in both black-box and white-box attack scenarios and show significant gains in comparison to state-of-the art defenses.Comment: Accepted at ICCV 201

Deeply Supervised Discriminative Learning for Adversarial Defense.

Deep neural networks can easily be fooled by an adversary with minuscule perturbations added to an input image. The existing defense techniques suffer greatly under white-box attack settings, where an adversary has full knowledge of the network and can iterate several times to find strong perturbations. We observe that the main reason for the existence of such vulnerabilities is the close proximity of different class samples in the learned feature space of deep models. This allows the model decisions to be completely changed by adding an imperceptible perturbation to the inputs. To counter this, we propose to class-wise disentangle the intermediate feature representations of deep networks, specifically forcing the features for each class to lie inside a convex polytope that is maximally separated from the polytopes of other classes. In this manner, the network is forced to learn distinct and distant decision regions for each class. We observe that this simple constraint on the features greatly enhances the robustness of learned models, even against the strongest white-box attacks, without degrading the classification performance on clean images. We report extensive evaluations in both black-box and white-box attack scenarios and show significant gains in comparison to state-of-the-art defenses

Deductive Verification of Chain-of-Thought Reasoning

Large Language Models (LLMs) significantly benefit from Chain-of-Thought (CoT) prompting in performing various reasoning tasks. While CoT allows models to produce more comprehensive reasoning processes, its emphasis on intermediate reasoning steps can inadvertently introduce hallucinations and accumulated errors, thereby limiting models' ability to solve complex reasoning tasks. Inspired by how humans engage in careful and meticulous deductive logical reasoning processes to solve tasks, we seek to enable language models to perform explicit and rigorous deductive reasoning, and also ensure the trustworthiness of their reasoning process through self-verification. However, directly verifying the validity of an entire deductive reasoning process is challenging, even with advanced models like ChatGPT. In light of this, we propose to decompose a reasoning verification process into a series of step-by-step subprocesses, each only receiving their necessary context and premises. To facilitate this procedure, we propose Natural Program, a natural language-based deductive reasoning format. Our approach enables models to generate precise reasoning steps where subsequent steps are more rigorously grounded on prior steps. It also empowers language models to carry out reasoning self-verification in a step-by-step manner. By integrating this verification process into each deductive reasoning stage, we significantly enhance the rigor and trustfulness of generated reasoning steps. Along this process, we also improve the answer correctness on complex reasoning tasks. Code will be released at https://github.com/lz1oceani/verify_cot

Synthesis and Properties of syn-[2.2](1,6)- and (4,6)Azulenophanes and Macrocyclic Azulenophanes

A regioselective synthesis of syn-[2.2](1,6)azulenophane (9) and syn-[2.2](4,6)azulenophane (12) is described. Azulenophane 9 is prepared by deprotonation of 1,2-bis(6-methylazulen-1-yl)ethane (5), followed by oxidative coupling of the initially formed dilithium salt 8 with iodine under high-dilution conditions in 17% yield, along with the macrocyclic [2.2.2.2](1,6)azulenophane (10) (3%), and [2.2.2.2.2.2](1,6)azulenophane (11) (1.5%). The azulenophane 12 and the macrocyclic [2.2.2.2](4,6)azulenophane (13) are obtained by coupling of the dianion of 1,2-bis(4-methylazulen-6-yl)ethane (14). The structural assignments of the title compounds are based on their spectral data. Protonation of 9 furnishes the mono- and dications 24 and 25, respectively, of which the first exhibits a charge-transfer band in its electronic spectrum, indicating a transannular interaction between the protonated and unprotonated azulene units. Protonation of 12 yields the mono- and dications 26 and 27, respectively. In contrast to 24, no new band due to an intramolecular transannular charge-transfer interaction is observed in the electronic spectrum of 26, and this is due to an insufficient overlap between the protonated and unprotonated azulene decks in 26. Vilsmeier formylation of 9 with 1.5 mol equivalents of phosphoryl chloride in DMF at room temp. yields 3-formyl-syn-[2.2](1,6)azulenophane (28) in 15% yield. Under the same reaction conditions a double formylation of 9 with 3 mol equivalents of phosphoryl chloride leads to 3,3′-diformyl-syn-[2.2](1,6)azulenophane (29) in 42% yield. The aminomethylation of 9 with paraformaldehyde and N, N, N′, N′-tetramethyldiaminomethane in the presence of acetic acid furnishes the Mannich bases 3-N, N-dimethylaminomethyl-syn-[2.2](1,6)azulenophane (30) and 3,3′-bis(N, N-dimethylaminomethyl)-syn-[2.2](1,6)azulenophane (31) in 40% and 46% yields, respectively

Integrated Care in England - what can we Learn from a Decade of National Pilot Programmes?

INTRODUCTION: For more than a decade the English NHS has pursued integrated care through three national pilot programmes. The independent evaluators of these programmes here identify several common themes that inform the development of integrated care. DESCRIPTION: The three pilot programmes shared the aim of better coordination between hospital and community-based health services and between health and social care. Each programme recruited local pilot sites that designed specific interventions to support inter-professional and inter-organisational collaboration.The pilots were highly heterogenous and results varied both within and between the three programmes. While staff were generally positive about their achievements, pilots had mixed success especially in reducing unplanned hospital admissions. Common facilitators to achieving pilots' objectives included effective senior leadership and shared values, simple interventions and additional funding. Barriers included short timescales, poor professional engagement, information and data sharing problems, and conflicts with changing national policy. DISCUSSION: There was little stable or shared understanding of what 'integrated care' meant resulting in different practices and priorities. An increasing focus on reducing unplanned hospital use among national sponsors created a mismatch in expectations between local and national actors. CONCLUSION: Pilots in all three national programmes made some headway against their objectives but were limited in their impact on unplanned hospital admissions

contribution of individual amino acids within mhc molecule or antigenic peptide to tcr ligand potency

The TCR recognition of peptides bound to MHC class II molecules is highly flexible in some T cells. Although progress has been made in understanding the interactions within the trimolecular complex, to what extent the individual components and their amino acid composition contribute to ligand recognition by individual T cells is not completely understood. We investigated how single amino acid residues influence Ag recognition of T cells by combining several experimental approaches. We defined TCR motifs for CD4+ T cells using peptide synthetic combinatorial libraries in the positional scanning format (PS-SCL) and single amino acid-modified peptide analogues. The similarity of the TCR motifs defined by both methods and the identification of stimulatory antigenic peptides by the PS-SCL approach argue for a contribution of each amino acid residue to the overall potency of the antigenic peptide ligand. In some instances, however, motifs are formed by adjacent amino acids, and their combined influence is superimposed on the overall contribution of each amino acid within the peptide epitope. In contrast to the flexibility of the TCR to interact with different peptides, recognition was very sensitive toward modifications of the MHC-restriction element. Exchanges of just one amino acid of the MHC molecule drastically reduced the number of peptides recognized. The results indicate that a specific MHC molecule not only selects certain peptides, but also is crucial for setting an affinity threshold for TCR recognition, which determines the flexibility in peptide recognition for a given TCR