Does neurocognitive training have the potential to improve dietary self-care in type 2 diabetes? Study protocol of a double blind randomised controlled trial

Dietary self-care is a key element of self-management in type 2 diabetes. It is also the most difficult aspect of diabetes self-management. Adhering to long-term dietary goals and resisting immediate food desires requires top-down inhibitory control over subcortical impulsive and emotional responses to food. Practising simple neurocognitive tasks can improve inhibitory control and health behaviours that depend on inhibitory control, such as resisting alcohol consumption. It is yet to be investigated, however, whether neurocognitive training can improve dietary self-care in people with type 2 diabetes. The aim of this randomised controlled trial is to investigate whether web-based neurocognitive training can improve the ability of people with type 2 diabetes to resist tempting foods and better adhere to a healthy dietary regime

Robust changes and sources of uncertainty in the projected hydrological regimes of Swiss catchments

Projections of discharge are key for future water resources management. These projections are subject to uncertainties, which are difficult to handle in the decision process on adaptation strategies. Uncertainties arise from different sources such as the emission scenarios, the climate models and their post-processing, the hydrological models and natural variability. Here we present a detailed and quantitative uncertainty assessment, based on recent climate scenarios for Switzerland (CH2011 data set) and covering catchments representative for mid-latitude alpine areas. This study relies on a particularly wide range of discharge projections resulting from the factorial combination of 3 emission scenarios, 10 to 20 regional climate models, 2 post-processing methods and 3 hydrological models of different complexity. This enabled us to decompose the uncertainty in the ensemble of projections using analyses of variance (ANOVA). We applied the same modeling setup to 6 catchments to assess the influence of catchment characteristics on the projected streamflow and focused on changes in the annual discharge cycle. The uncertainties captured by our setup originate mainly from the climate models and natural climate variability, but the choice of emission scenario plays a large role by the end of the century. The respective contribution of the different sources of uncertainty varied strongly among the catchments. The discharge changes were compared to the estimated natural decadal variability, which revealed that a climate change signal emerges even under the lowest emission scenario (RCP2.6) by the end of the century. Limiting emissions to RCP2.6 levels would nevertheless reduce the largest regime changes at the end of the 21st century by approximately a factor of two, in comparison to impacts projected for the high emission scenario SRES A2. We finally show that robust regime changes emerge despite the projection uncertainty. These changes are significant and are consistent across a wide range of scenarios and catchments. We propose their identification as a way to aid decision-making under uncertainty

The abilities of improved schizophrenia patients to work and live independently in the community: a 10-year long-term outcome study from Mumbai, India

Background: The outcome of schizophrenia has several determinants. Socioecological factors, particularly living conditions, migration, community and culture, not only affect the level of risk but also the outcome. Mega cities around the world show a unique socioecological condition that has several challenges for mental health. The present study reports on the long-term status of patients with schizophrenia in such a mega city: Mumbai, India. Aim This study aims to reveal the long-term outcome of patients suffering from schizophrenia with special reference to clinical symptoms and social functioning. Methods: The cohort for this study was drawn from a 10-year follow-up of first episode schizophrenia. Patients having completed 10 years of consistent treatment after first hospitalisation were assessed on psychopathological and recovery criteria. Clinical as well as social parameters of recovery were evaluated. Descriptive statistics with 95% confidence intervals are provided. Results: Of 200 patients recruited at the beginning of this study, 122 patients (61%) were present in the city of Mumbai at the end of 10-year follow-up study period. Among 122 available patients, 101 patients (50.5%) were included in the assessment at the end of 10-year follow-up study period, 6 patients (3.0%) were excluded from the study due to changed diagnosis, and 15 patients (7.5%) were excluded due to admission into long-term care facilities. This indicates that 107 out of 122 available patients (87.7%) were living in the community with their families. Out of 101 (50.5%) patients assessed at the end of 10 years, 61 patients (30.5%) showed improved recovery on the Clinical Global Impression Scale, 40 patients (20%) revealed no improvement in the recovery, 43 patients (72.9%) were able to live independently, and 24 patients (40%) were able to find employment. Conclusions: With 10 years of treatment, the recovery rate among schizophrenia patients in Mumbai was 30.5%. Among the patients, 87.7% of patients lived in the community, 72.9% of patients lived independently, and 40% of patients obtained employment. However, 60% of patients were unable to return to work, which highlights the need for continued monitoring and support to prevent the deterioration of health in these patients. It is likely that socioecological factors have played a role in this outcome

The role of emotions and physiological arousal in modulating impulsive behaviour.

Impulsivity received considerable attention in the context of drug misuse and certain neuropsychiatric conditions. Because of its great health and well-being importance, it is crucial to understand factors which modulate impulsive behaviour. As a growing body of literature indicates the role of emotional and physiological states in guiding our actions and decisions, we argue that current affective state and physiological arousal exert a significant influence on behavioural impulsivity. As 'impulsivity' is a heterogeneous concept, in this paper, we review key theories of the topic and summarise information about distinct impulsivity subtypes and their methods of assessment, pointing out to the differences between the various components of the construct. Moreover, we review existing literature on the relationship between emotional states, arousal and impulsive behaviour and suggest directions for future research

Impact of a targeted direct marketing price promotion intervention (Buywell) on food purchasing behaviour by low income consumers:a randomised controlled trial

Background: Price promotions are a promising intervention for encouraging healthier food purchasing. We aimed to assess the impact of a targeted direct marketing price promotion combined with healthy eating advice and recipe suggestions on the purchase of selected healthier foods by low income consumers.  Methods: We conducted a randomised controlled trial (n = 53 367) of a direct marketing price promotion (Buywell) combined with healthy eating advice and recipe suggestions for low income consumers identified as ‘less healthy’ shoppers. Impact was assessed using electronic point of sale data for UK low income shoppers before, during and after the promotion.  Results: The proportion of customers buying promoted products in the intervention month increased by between 1.4% and 2.8% for four of the five products. There was significantly higher uptake in the promotion month (P < 0.001) for the intervention group than would have been expected on the basis of average uptake in the other months. When product switching was examined for semi-skimmed/skimmed milk, a modest increase (1%) was found in the intervention month of customers switching from full-fat to low-fat milk. This represented 8% of customers who previously bought only full-fat milk. The effects were generally not sustained after the promotion period.  Conclusions: Short-term direct marketing price promotions combined with healthy eating advice and recipe suggestions targeted at low income consumers are feasible and can have a modest impact on short-term food-purchasing behaviour, although further approaches are needed to help sustain these changes

A palaeoenvironmental reconstruction of the Middle Jurassic of Sardinia (Italy) based on integrated palaeobotanical, palynological and lithofacies data assessment

During the Jurassic, Sardinia was close to continental Europe. Emerged lands started from a single island forming in time a progressively sinking archipelago. This complex palaeogeographic situation gave origin to a diverse landscape with a variety of habitats. Collection- and literature-based palaeobotanical, palynological and lithofacies studies were carried out on the Genna Selole Formation for palaeoenvironmental interpretations. They evidence a generally warm and humid climate, affected occasionally by drier periods. Several distinct ecosystems can be discerned in this climate, including alluvial fans with braided streams (Laconi-Gadoni lithofacies), paralic swamps and coasts (Nurri-Escalaplano lithofacies), and lagoons and shallow marine environments (Ussassai-Perdasdefogu lithofacies). The non-marine environments were covered by extensive lowland and a reduced coastal and tidally influenced environment. Both the river and the upland/hinterland environments are of limited impact for the reconstruction. The difference between the composition of the palynological and palaeobotanical associations evidence the discrepancies obtained using only one of those proxies. The macroremains reflect the local palaeoenvironments better, although subjected to a transport bias (e.g. missing upland elements and delicate organs), whereas the palynomorphs permit to reconstruct the regional palaeoclimate. Considering that the flora of Sardinia is the southernmost of all Middle Jurassic European floras, this multidisciplinary study increases our understanding of the terrestrial environments during that period of time

Data-driven decision support for product change management : Making explainable classifications of product change requests at Scania using machine learning methods

Decision making is a big part of our day-to-day lives, both personal and professional. A good decision support can provide a decision process with high quality, efficiency and consistency. In recent years, machine learning has shown outstanding capacity for making complex processes understandable and provide decision support. But what good is this decision support if it is not trusted? Our work tries to improve the usage of machine learning models by making their results more understandable and trustworthy. In this thesis, we investigate the decisions in the Product Development (PD) process at Scania. Two important steps in the PD process is to prioritize a Product Change Request (PCR) and decide if it should be realized or not. Our main objective is to build machine learning models that can be incorporated in this process and help with the decision making. In order to choose the most suitable model, different machine learning models are trained on historical data. The model with the best performance is chosen and can be used to make predictions on new PCRs. The model that performed best when deciding the priority of a given PCR was Extreme Gradient Boosting (XGB), which achieved a F1 score of 46.6% and an accuracy of 48.0%. However, we found that the data was not suitable for making classifications regarding the priorities. The model that performed the best when deciding if a PCR should be realized or not was the random forest, which achieved a F1 score of 67.4% and an accuracy of 79.4%. We found that better classifications could be made regarding if a PCR should be realized or not when additional data was added to the model, and we therefore recommend changes to the collection and storage of data. The random forest achieved a F1 score of 73.5% and an accuracy of 83.8% with the additional data from attachments. We also explain and visualize how the random forest makes its classification and how each feature from the PCRs affect the classification. This is important in order to improve the trust in the decision support provided by the model. Att ta beslut är en stor del av våra dagliga liv, både personligt och professionellt. Ett bra beslutsstöd kan skapa en beslutsprocess med hög kvalitet, effektivitet och stabilitet. Under de senaste åren har maskininlärning blivit ett viktigt verktyg för att förstå komplexa processer och skapa beslutsstöd. Men vilken nytta gör detta beslutsstöd om människor inte litar på det? Vårt arbete försöker att hantera detta problem och göra resultaten från maskininlärningsmodeller mer förståeliga och tillförlitliga. I den här rapporten undersöker vi besluten som tas i processen för produktutveckling hos Scania. Två viktiga steg i denna process är att prioritera föreslagna produktförändringar och att bestämma ifall dessa ska genomföras eller inte. Vårt huvudmål är att bygga maskininlärningsmodeller som kan användas i denna process och hjälpa till vid beslutstagandet. För att kunna välja den lämpligaste modellen så tränas olika maskininlärningsmodeller på historiska data. Modellen som presterar bäst väljs och kan användas för att förutsäga besluten för nya föreslagna produktförändringar. Den modell som lyckades bäst med att förutsäga vilken prioritet som en föreslagen produktförändring ska ha var Extreme Gradient Boosting (XGB) som uppnådde ett F1-score på 46,6% och en träffsäkerhet på 48,0%. Vi såg däremot att den data som fanns inte var lämplig för att göra klassificeringar gällande prioriteringen. Den modell som lyckades bäst med att bestämma ifall en föreslagen produktförändring borde genomföras eller inte var random forest, som uppnådde ett F1-score på 67,4% och en träffsäkerhet på 79,4%. Vi visar att bättre klassificeringar kan göras gällande om en föreslagen produktförändring ska genomföras eller inte när mer data läggs till i modellen, och vi kan därmed föreslå förändringar av insamlingen och lagringen av data. Random forest uppnådde ett F1-score på 73,5% och en träffsäkerhet på 83,8% med data insamlat från bilagor. Vi förklarar och visar även hur random forest gör sin klassificering och hur varje faktor från den föreslagna produktförändringen påverkar klassificeringen. Detta är viktigt för att kunna öka förtroendet för det beslutsstöd som modellen ger

Homomorfisk kryptering för ljudkonferenssamtal

Homomorphic encryption (HE) enables computations on encrypted data making it possible to perform calculations on a server without sharing the secret key for decryption. HE is relatively new and has seen significant improvements in recent years in terms of speed of encryption, decryption, operations, and the number of operations possible to perform in a row without damaging the ciphertext. These improvements open up new possibilities, such as using HE in voice over IP (VoIP) and still being able to mix audio streams at the server without decrypting them, creating a scalable and secure application.  This thesis evaluates the performance of three HE schemes, BGV, BFV, and CKKS, implemented by the open-source library Palisade and compares their performance to a non-HE scheme AES in terms of encryption time, decryption time and end-to-end latency. Furthermore, the performance of mixing with HE-encrypted audio files is evaluated. The work is a proof-of-concept that allows the user to send audio files of different sample rates and batch sizes to compare the performance. It also investigates the Quality of Experience by measuring the audio quality after the mixing, using PESQ and POLQA. The results show that BGV performs almost as good as AES for higher batch sizes, while BFV performs almost as good in most cases and trails behind in others. CKKS, on the other hand, is the slowest scheme but is still fast enough in some cases to be considered a possible encryption scheme. Furthermore, the tests show that the HE schemes do not decrease the listening quality much according to PESQ and POLQA, as all tests concluded a result that is considered good or excellent. The number of files being mixed had a negative impact on narrowband and wideband audio streams, while it did not affect superwideband and fullband

Homomorfisk kryptering för ljudkonferenssamtal

Homomorphic encryption (HE) enables computations on encrypted data making it possible to perform calculations on a server without sharing the secret key for decryption. HE is relatively new and has seen significant improvements in recent years in terms of speed of encryption, decryption, operations, and the number of operations possible to perform in a row without damaging the ciphertext. These improvements open up new possibilities, such as using HE in voice over IP (VoIP) and still being able to mix audio streams at the server without decrypting them, creating a scalable and secure application.  This thesis evaluates the performance of three HE schemes, BGV, BFV, and CKKS, implemented by the open-source library Palisade and compares their performance to a non-HE scheme AES in terms of encryption time, decryption time and end-to-end latency. Furthermore, the performance of mixing with HE-encrypted audio files is evaluated. The work is a proof-of-concept that allows the user to send audio files of different sample rates and batch sizes to compare the performance. It also investigates the Quality of Experience by measuring the audio quality after the mixing, using PESQ and POLQA. The results show that BGV performs almost as good as AES for higher batch sizes, while BFV performs almost as good in most cases and trails behind in others. CKKS, on the other hand, is the slowest scheme but is still fast enough in some cases to be considered a possible encryption scheme. Furthermore, the tests show that the HE schemes do not decrease the listening quality much according to PESQ and POLQA, as all tests concluded a result that is considered good or excellent. The number of files being mixed had a negative impact on narrowband and wideband audio streams, while it did not affect superwideband and fullband