Fundamentals of a Novel Debugging Mechanism for Orchestrated Cloud Infrastructures with Macrosteps and Active Control

In Infrastructure-as-a-Service (IaaS) clouds, the development process of a ready-to-use and reliable infrastructure might be a complex task due to the interconnected and dependent services that are deployed (and operated later on) in a concurrent way on virtual machines. Different timing conditions may change the overall initialisation method, which can lead to abnormal behaviour or failure in the non-deterministic environment. The overall motivation of our research is to improve the reliability of cloud-based infrastructures with minimal user interactions and significantly accelerate the time-consuming debugging process. This paper focuses on the behaviour of cloud-based infrastructures during their deployment phase and introduces the adaption of a replay, and active control enriched debugging technique, called macrostep, in the field of cloud orchestration in order to provide support for developers troubleshooting deployment-related errors. The fundamental macrostep mechanisms, including the generation of collective breakpoint sets as well as the traversal method for such consistent global states, have been combined with the Occopus cloud orchestrator and the Neo4J graph database. The paper describes the novel approach, the design choices as well as the implementation of the experimental debugger tool with a use case for validation purposes by providing some preliminary numerical results.

His Brain Has Just Gone Haywire: the Development of Children and Young People's Concepts of Mental Illness

<p>This thesis examines children and young people's ideas about mental illness. Frequently, previous research in this area has suffered from methodological flaws or a limited theoretical framework. Qualitative methodology was utilised in this thesis in order to both gather the range of ideas that children have about mental illness, and to propose a theoretical model to explain the development of these ideas. In the first study, 63 children (comprising 4 age groups: 6 - 7, 9 - 10, 12 - 13, and 16 - 18 years old) participated in focus group discussions. Groups were presented with 3 illustrated vignettes, each depicting a story about an adult with a mental health problem (schizophrenia, agoraphobia, or depression). A thematic analysis was used to examine the ideas that children expressed in these discussions. Analysis found that children have a wide range of ways of explaining the characters' behaviours. Children and young people's ideas were grouped into 5 main categories: 'medical explanationsà ¢ , 'psychiatric explanations', 'abnormal behaviour explanations', 'psychological explanations', and 'event explanations'. Following this, a second study was conducted to focus on children's ideas about causes and treatments for mental illness. 36 children (ages 9 - 10, 12 - 13, and 16 - 18) were interviewed individually. Participants were presented the same 3 vignettes and asked to create a story that explains why each character has their problem and how their problem is resolved. Grounded theory methods were used to analyse the stories, with 6 primary categories and 1 secondary category (' psychological explanations') emerging. All stories included a cause from one of the 6 primary categories, and sometimes that primary category also led to a thinking problem (from the secondary category). Resolutions to the stories either came from the same primary category as the suggested cause, or alternatively, treatment came from one of the treatments included in the secondary category ('think or act differently', 'counselling', or 'support from others'). The primary categories were 'event' (problem was due to an external event happening, and resolution comes from an external event occurring); 'physiological' (the problem is seen as a medical problem, and treatment came from doctors); 'neurological / psychiatric' (characters have problems with their brains or a diagnostic label, resolutions include psychiatric medication, hospitalisation, and negative outcomes); 'drug' problems; 'spiritual' (discussion related to ghosts or religion); and 'responsibility' (the character had done something wrong, and must fix it to resolve their problem). Further analysis then compared the data from both studies with previous theoretical literature. It is argued that as children grow older they develop a concept of mental illness, which they can then use when discussing vignettes or understanding abnormal behaviour. This domain-specific development occurs throughout late childhood and adolescence as children incorporate information they have learned from families, schools, and media, and build on pre-existing domains (in particular, naive psychology and naive biology). Evidence from the current study is used to support this proposed model, and implications for future research, school curriculum, and helping children with mentally ill relatives are discussed.</p>

His Brain Has Just Gone Haywire: the Development of Children and Young People's Concepts of Mental Illness

<p>This thesis examines children and young people's ideas about mental illness. Frequently, previous research in this area has suffered from methodological flaws or a limited theoretical framework. Qualitative methodology was utilised in this thesis in order to both gather the range of ideas that children have about mental illness, and to propose a theoretical model to explain the development of these ideas. In the first study, 63 children (comprising 4 age groups: 6 - 7, 9 - 10, 12 - 13, and 16 - 18 years old) participated in focus group discussions. Groups were presented with 3 illustrated vignettes, each depicting a story about an adult with a mental health problem (schizophrenia, agoraphobia, or depression). A thematic analysis was used to examine the ideas that children expressed in these discussions. Analysis found that children have a wide range of ways of explaining the characters' behaviours. Children and young people's ideas were grouped into 5 main categories: 'medical explanationsà ¢ , 'psychiatric explanations', 'abnormal behaviour explanations', 'psychological explanations', and 'event explanations'. Following this, a second study was conducted to focus on children's ideas about causes and treatments for mental illness. 36 children (ages 9 - 10, 12 - 13, and 16 - 18) were interviewed individually. Participants were presented the same 3 vignettes and asked to create a story that explains why each character has their problem and how their problem is resolved. Grounded theory methods were used to analyse the stories, with 6 primary categories and 1 secondary category (' psychological explanations') emerging. All stories included a cause from one of the 6 primary categories, and sometimes that primary category also led to a thinking problem (from the secondary category). Resolutions to the stories either came from the same primary category as the suggested cause, or alternatively, treatment came from one of the treatments included in the secondary category ('think or act differently', 'counselling', or 'support from others'). The primary categories were 'event' (problem was due to an external event happening, and resolution comes from an external event occurring); 'physiological' (the problem is seen as a medical problem, and treatment came from doctors); 'neurological / psychiatric' (characters have problems with their brains or a diagnostic label, resolutions include psychiatric medication, hospitalisation, and negative outcomes); 'drug' problems; 'spiritual' (discussion related to ghosts or religion); and 'responsibility' (the character had done something wrong, and must fix it to resolve their problem). Further analysis then compared the data from both studies with previous theoretical literature. It is argued that as children grow older they develop a concept of mental illness, which they can then use when discussing vignettes or understanding abnormal behaviour. This domain-specific development occurs throughout late childhood and adolescence as children incorporate information they have learned from families, schools, and media, and build on pre-existing domains (in particular, naive psychology and naive biology). Evidence from the current study is used to support this proposed model, and implications for future research, school curriculum, and helping children with mentally ill relatives are discussed.</p>

Bayesian network model to distinguish between intentional attacks and accidental technical failures: a case study of floodgates

Water management infrastructures such as floodgates are critical and increasingly operated by Industrial Control Systems (ICS). These systems are becoming more connected to the internet, either directly or through the corporate networks. This makes them vulnerable to cyber-attacks. Abnormal behaviour in floodgates operated by ICS could be caused by both (intentional) attacks and (accidental) technical failures. When operators notice abnormal behaviour, they should be able to distinguish between those two causes to take appropriate measures, because for example replacing a sensor in case of intentional incorrect sensor measurements would be ineffective and would not block corresponding the attack vector. In the previous work, we developed the attack-failure distinguisher framework for constructing Bayesian Network (BN) models to enable operators to distinguish between those two causes, including the knowledge elicitation method to construct the directed acyclic graph and conditional probability tables of BN models. As a full case study of the attack-failure distinguisher framework, this paper presents a BN model constructed to distinguish between attacks and technical failures for the problem of incorrect sensor measurements in floodgates, addressing the problem of floodgate operators. We utilised experts who associate themselves with the safety and/or security community to construct the BN model and validate the qualitative part of constructed BN model. The constructed BN model is usable in water management infrastructures to distinguish between intentional attacks and accidental technical failures in case of incorrect sensor measurements. This could help to decide on appropriate response strategies and avoid further complications in case of incorrect sensor measurements.

CRITICAL ANALYSIS OF RAJASWALA CHARYA IN RELATION WITH ATTENTION DEFICIT HYPERACTIVITY DISORDER (ADHD) IN CHILDREN - A SURVEY STUDY

Attention deficit hyperactivity disorder or ADHD is the commonest neurological disorder that affects the behaviour of children.1 World Health Organization put forth that, mental disorders are to shoot up by 50% in 2020 at international level. Indian studies rate the psychopathology among children as 5-15% and ADHD has the highest incidence among all the other developmental disorders2. There is no disease by the name ADHD described in Ayurveda, but some conditions of abnormal behaviour can be screened from Ayurvedic literature like Anavasthita Chittatva3, Manovibhrama4, Buddhivibhrama5, Smritivibhrama 4, Sheelavibhrama6 Cheshtavibrama7, and Acharavibhrama. It is found that emergence of the ADHD does not follow a single responsible factor7 and thus a single line of treatment does not cure it7,2. The prevalence of ADHD is increased recently, and people started turning to alternative and complementary medicine especially Ayurveda, it is worthwhile to understand the probable aetiology to prevent the emergence of disease. It is known that the Rajaswala period is the largest and most important period among women's life and need to be healthy in this phase to have a better progeny. But in the present era, women are in hurry to reach the mainstream of society and under much physical and mental stress ends up with lack of care on their health even during menstruation which may lead to ill effect in later life8. This study is to put light on the importance of following regimens and avoiding Apathyas especially during menstruation explained in Ayurvedic classics concerning ADHD. Keywords: Rajaswala, ADHD, paricharya

Predicting mortality among septic patients presenting to the emergency department–a cross sectional analysis using machine learning

Background Sepsis is a life-threatening condition, causing almost one fifth of all deaths worldwide. The aim of the current study was to identify variables predictive of 7- and 30-day mortality among variables reflective of the presentation of septic patients arriving to the emergency department (ED) using machine learning. Methods Retrospective cross-sectional design, including all patients arriving to the ED at Södersjukhuset in Sweden during 2013 and discharged with an International Classification of Diseases (ICD)-10 code corresponding to sepsis. All predictions were made using a Balanced Random Forest Classifier and 91 variables reflecting ED presentation. An exhaustive search was used to remove unnecessary variables in the final model. A 10-fold cross validation was performed and the accuracy was described using the mean value of the following: AUC, sensitivity, specificity, PPV, NPV, positive LR and negative LR. Results The study population included 445 septic patients, randomised to a training (n = 356, 80%) and a validation set (n = 89, 20%). The six most important variables for predicting 7-day mortality were: “fever”, “abnormal verbal response”, “low saturation”, “arrival by emergency medical services (EMS)”, “abnormal behaviour or level of consciousness” and “chills”. The model including these variables had an AUC of 0.83 (95% CI: 0.80–0.86). The final model predicting 30-day mortality used similar six variables, however, including “breathing difficulties” instead of “abnormal behaviour or level of consciousness”. This model achieved an AUC = 0.80 (CI 95%, 0.78–0.82). Conclusions The results suggest that six specific variables were predictive of 7- and 30-day mortality with good accuracy which suggests that these symptoms, observations and mode of arrival may be important components to include along with vital signs in a future prediction tool of mortality among septic patients presenting to the ED. In addition, the Random Forests appears to be a suitable machine learning method on which to build future studies.

Natural kinds of mental disorder

Are mental disorders (autism, ADHD, schizophrenia) natural kinds or socially constructed categories? What is at stake if either of these views prove to be true? This paper offers a qualified defence for the view that there may be natural kinds of mental disorder, but also that the implications of this claim are generally overestimated. Especially concerns about over-inclusiveness of diagnostic categories and medicalisation of abnormal behaviour are not addressed by the debate. To arrive at these conclusions the paper opens with a discussion of kind formation in science, followed by an analysis of natural kinds. Seven principled and empirically informed objections to the possibility of natural kinds of mental disorder are considered and rejected. The paper ends with a reflection on diagnostics of mental health problems that don’t fall into natural kinds. Despite the defence of the possibility of natural kinds of mental disorder, this is likely to be the majority of cases.

Philippe Artières, Un Séminariste assassin: L’affaire Bladier, 1905

At the end of the nineteenth and in the early years of the twentieth century, encouraging violent criminals to write their life stories became an accepted tool of forensic medicine. The autobiographical texts which emerged became vital building blocks in the psychological diagnosis of the subject. One of the leading international exponents of this method was the Lyon-based professor Alexandre Lacassagne, who developed a science of criminal anthropology guided by the principles of heredity and phrenology (the idea that mental functions could be precisely located in specific parts of the brain). Lacassagne was fascinated by abnormal behaviour and urged the inmates of Lyon prisons to write their autobiographies. He took a paternal interest in them, studied their tattoos, and used their life writing as a key to understanding the criminal personality. Philippe Artières has been working on Lacassagne’s papers for over 25 years, and they formed the basis of his previous work Le livre des vies coupables: autobiographies de criminels, 1896-1909 (The book of guilty lives) (Paris, 2000 and 2014). In this new book, he revisits one particularly disturbing case – the Bladier affair of 1905.

Basic Needs in Horses?—A Literature Review

Every animal species has particular environmental requirements that are essential for its welfare, and when these so-called “basic needs” are not fulfilled, the animals suffer. The basic needs of horses have been claimed to be social contact, social companionship, free movement and access to roughage. To assess whether horses suffer when one or more of the four proposed basic needs are restricted, we examined several studies (n = 38) that reported behavioural and physiological reactions to these restrictions. We assigned the studies according to the four types of responses investigated: (a) Stress, (b) Active, (c) Passive, and (d) Abnormal Behaviour. Furthermore, the number of studies indicating that horses reacted to the restrictions were compared with the number of studies reporting no reaction. The limited number of studies available on single management restrictions did not allow conclusions to be drawn on the effect of each restriction separately, especially in the case of social companionship. However, when combinations of social contact, free movement and access to roughage were restricted, many of the horses had developed responses consistent with suffering. Passive Responses, indicating acute suffering, and Abnormal Behaviour, indicating suffering currently or at some time in the past, were especially clearly demonstrated. This provides further evidence of the usefulness of assessing behavioural parameters in combination with physiological measurements when evaluating horse welfare. This meta-analysis of the literature confirms that it is justified to claim that social contact, free movement and access to roughage are basic needs in horses.