Meson-meson correlations in baryon-baryon and antibaryon-baryon interactions

Recent work of the J\"ulich group about the role of meson-meson correlations in baryon-baryon and antibaryon-baryon interactions is reviewed.Comment: Lecture given at the Erice School 1995, TEX, 10 pages, 15 figure

Correlated ππ\pi\pi and KKˉK\bar K exchange in the baryon-baryon interaction

A dynamical model for correlated two-pion and two-kaon exchange in the baryon- baryon interaction is presented, both in the scalar-isoscalar ($\sigma$) and the vector-isovector ($\rho$) channel. The correlations between the two pseudoscalar mesons are taken into account by means of $\pi\pi - K\bar K$ amplitudes derived from a meson-exchange model, which is in line with the empirical $\pi\pi$ data. It is found that correlated $K\bar K$ exchange plays an important role in the $\sigma$-channel for baryon-baryon states with non- vanishing strangeness. The strength of correlated $\pi\pi$ plus $K\bar K$ exchange in the $\sigma$-channel decreases with the strangeness of the baryon- baryon system becoming more negative. The results for correlated $\pi\pi$- exchange in the vector-isovector channel deviate from what is expected in the naive SU(3) picture for genuine $\rho$-exchange. Shortcomings of a simplified description in terms of sharp mass $\sigma$- and $\rho$-exchange are pointed out.Comment: 51 pages, Latex file, figures available from [email protected]

Distinctive neuropsychological profiles differentiate patients with functional memory disorder from patients with amnestic-mild cognitive impairment

OBJECTIVES: Patients with functional memory disorder (FMD) report significant memory failures in everyday life. Differentiating these patients from those with memory difficulties due to early stage neurodegenerative conditions is clinically challenging. The current study explored whether distinctive neuropsychological profiles could be established, suitable to differentiate patients with FMD from healthy individuals and those experiencing amnestic mild cognitive impairment (a-MCI). METHODS: Patients with a clinical diagnosis of FMD were compared with patients with a-MCI, and healthy matched controls on several tests assessing different cognitive functions. Patients with clinically established mood disorders were excluded. Patients with FMD and a-MCI were broadly comparable on the level of their subjective memory complaints as assessed by clinical interview. RESULTS: The neuropsychological profile of the FMD patients, although they expressed subjective memory and attention concerns during their clinical interview was distinct from patients with a-MCI on tests of memory [semantic fluency, age of acquisition (AoA) analysis of semantic fluency, verbal and non-verbal memory]. FMD patients did not differ significantly from healthy controls, but their scores on the letter fluency and digit cancellation tasks were not significantly different from those of the a-MCI patients indicating a possible sub-threshold deficit on these tasks. CONCLUSION: Whilst subjective complaints are common within the FMD population, no objective impairment could be detected, even on a sensitive battery of tasks designed to detect subtle deficits caused by an early neurodegenerative brain disease. This study indicates that FMD patients can be successfully differentiated from patients with neurodegenerative memory decline by characterising their neuropsychological profile

An avatar-based system for identifying individuals likely to develop dementia

This paper presents work on developing an automatic dementia screening test based on patients’ ability to interact and communicate — a highly cognitively demanding process where early signs of dementia can often be detected. Such a test would help general practitioners, with no specialist knowledge, make better diagnostic decisions as current tests lack specificity and sensitivity. We investigate the feasibility of basing the test on conversations between a ‘talking head’ (avatar) and a patient and we present a system for analysing such conversations for signs of dementia in the patient’s speech and language. Previously we proposed a semi-automatic system that transcribed conversations between patients and neurologists and extracted conversation analysis style features in order to differentiate between patients with progressive neurodegenerative dementia (ND) and functional memory disorders (FMD). Determining who talks when in the conversations was performed manually. In this study, we investigate a fully automatic system including speaker diarisation, and the use of additional acoustic and lexical features. Initial results from a pilot study are presented which shows that the avatar conversations can successfully classify ND/FMD with around 91% accuracy, which is in line with previous results for conversations that were led by a neurologist

Toward the Automation of Diagnostic Conversation Analysis in Patients with Memory Complaints.

BACKGROUND: The early diagnosis of dementia is of great clinical and social importance. A recent study using the qualitative methodology of conversation analysis (CA) demonstrated that language and communication problems are evident during interactions between patients and neurologists, and that interactional observations can be used to differentiate between cognitive difficulties due to neurodegenerative disorders (ND) or functional memory disorders (FMD). OBJECTIVE: This study explores whether the differential diagnostic analysis of doctor-patient interactions in a memory clinic can be automated. METHODS: Verbatim transcripts of conversations between neurologists and patients initially presenting with memory problems to a specialist clinic were produced manually (15 with FMD, and 15 with ND). A range of automatically detectable features focusing on acoustic, lexical, semantic, and visual information contained in the transcripts were defined aiming to replicate the diagnostic qualitative observations. The features were used to train a set of five machine learning classifiers to distinguish between ND and FMD. RESULTS: The mean rate of correct classification between ND and FMD was 93% ranging from 97% by the Perceptron classifier to 90% by the Random Forest classifier.Using only the ten best features, the mean correct classification score increased to 95%. CONCLUSION: This pilot study provides proof-of-principle that a machine learning approach to analyzing transcripts of interactions between neurologists and patients describing memory problems can distinguish people with neurodegenerative dementia from people with FMD

Memory difficulties are not always a sign of incipient dementia: a review of the possible causes of loss of memory efficiency

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Charge Symmetry Breaking and QCD

Charge symmetry breaking (CSB) in the strong interaction occurs because of the difference between the masses of the up and down quarks. The use of effective field theories allows us to follow this influence of confined quarks in hadronic and nuclear systems. The progress in observing and understanding CSB is reviewed with particular attention to the recent successful observations of CSB in measurements involving the production of a single neutral pion and to the related theoretical progress.Comment: 41 pages, 10 figures, for Nov. 2006 edition Annual Review of Nuclear and Particle Physic

Towards diagnostic conversational profiles of patients presenting with dementia or functional memory disorders to memory clinics

Objective: This study explores whether the profile of patients' interactional behaviour in memory clinic conversations with a doctor can contribute to the clinical differentiation between functional memory disorders (FMD) and memory problems related to neurodegenerative diseases. Methods: Conversation Analysis of video recordings of neurologists' interactions with patients attending a specialist memory clinic. "Gold standard" diagnoses were made independently of CA findings by a multi-disciplinary team based on clinical assessment, neuropsychological testing and brain imaging. Results: Two discrete conversational profiles for patients with memory complaints emerged, including (i) who attends the clinic (i.e., whether or not patients are accompanied), and (ii) patients' responses to neurologists' questions about memory problems, such as difficulties with compound questions and providing specific and elaborated examples and frequent "I don't know" responses. Conclusion: Specific communicative difficulties are characteristic of the interaction patterns of patients with a neurodegenerative pathology. Those difficulties are manifest in memory clinic interactions with neurologists, thereby helping to differentiate patients with dementia from those with FMD. Practical implications: Our findings demonstrate that conversational profiles based on patients' contributions to memory clinic encounters have diagnostic potential to assist the screening and referral process from primary care, and the diagnostic service in secondary care

The hyperon-nucleon interaction: conventional versus effective field theory approach

Hyperon-nucleon interactions are presented that are derived either in the conventional meson-exchange picture or within leading order chiral effective field theory. The chiral potential consists of one-pseudoscalar-meson exchanges and non-derivative four-baryon contact terms. With regard to meson-exchange hyperon-nucleon models we focus on the new potential of the Juelich group, whose most salient feature is that the contributions in the scalar--isoscalar (\sigma) and vector--isovector (\rho) exchange channels are constrained by a microscopic model of correlated \pi\pi and KKbar exchange.Comment: 28 pages, 8 figures, submitted to Lecture Notes in Physic