Reducing cloud infrastructure costs through task management

The transition of more and more companies from their own computing infrastructure to the clouds is due to a decrease in the cost of maintaining it, the broadest scalability, and the presence of a large number of tools for automating activities. Accordingly, cloud providers provide an increasing number of different computing resources and tools for working in the clouds. In turn, this gives rise to the problem of the rational choice of the types of cloud services in accordance with the peculiarities of the tasks to be solved. One of the most popular areas of effort for cloud consumers is to reduce rental costs. The main base of this direction is the use of spot resources. The article proposes a method for reducing the cost of renting computing resources in the cloud by dynamically managing the placement of computational tasks, which takes into account the possible underutilization of planned resources, the forecast of the appearance of spot resources and their cost. For each task, a state vector is generated that takes into account the duration of the task and the required deadline. Accordingly, for a suitable set of computing resources, an availability forecast vectors are formed at a given time interval, counting from the current moment in time. The technique proposes to calculate at each discrete moment of time the most rational option for placing the task on one of the resources and the delay in starting the task on it. The placement option and launch delays are determined by minimizing the rental cost function over the time interval using a genetic algorithm. One of the features of using spot resources is the auction mechanism for their provision by a cloud provider. This means that if there are more preferable rental prices from any consumer, then the provider can warn you about the disconnection of the resource and make this disconnection after the announced time. To minimize the consequences of such a shutdown, the technique involves preliminary preparation of tasks by dividing them into substages with the ability to quickly save the current results in memory and then restart from the point of stop. In addition, to increase the likelihood that the task will not be interrupted, a price forecast for the types of resources used is used and a slightly higher price is offered for the auction of the cloud provider, compared to the forecast. Using the example of using the Elastic Cloud Computing (EC2) environment of the cloud provider AWS, the effectiveness of the proposed method is shown.

Using clinical pathways to prospectively identify poor prognosis cancer patients: A preliminary analysis.

329 Background: Cancer patients in the last year of life may have different clinical needs and evolving goals of care. Helping clinicians consistently identify such patients in a systematic and prospective fashion, at a discrete moment in the care trajectory, is an important step towards optimizing the care of these patients. Methods: Physician medical directors for each clinical pathway at our institution were tasked with identifying nodes within their respective treatment pathways associated with poor prognosis, specifically a median overall survival of < 12 months. This information was embedded into the underlying data model of the pathways platform, allowing us to determine how often clinicians navigated through poor prognosis nodes. Results: Pathways medical directors identified 44 nodes associated with poor prognosis. Some of these nodes encompassed a broader set of patients (metastatic pancreatic cancer, any line), whereas others were more specific (metastatic non-small cell lung cancer, squamous cell histology, second line or beyond). For the period 3/11/20 – 5/31/21, clinicians navigated in the platform for 11,057 unique patients. Of these, 1,234 (11.1%) unique patients were associated with poor prognosis nodes. Such navigations were much more common in patients with solid tumors (table). Conclusions: A well-maintained clinical pathways program can be a mechanism for defining clinical settings associated with poor prognosis and for routinely identifying patients in these settings. By embedding this into the pathways data model, we can provide physicians with important reminders and resources related to goals of care conversations, supportive care resources, and appropriate treatment options and clinical trials.[Table: see text]

The episodic man: How a psychological biography of Donald J. Trump casts new light on empirical research into narrative identity

People make meaning through life narrative. The central thesis of my book-length psychological biography of Donald Trump is that the 45th president of the United States defied this general meaning-making tendency and epitomized instead the episodic man. Like no other president in modern history, Trump seems to be nearly devoid of a narrative identity, which is an internalized and evolving story of the self that reconstructs the personal past and imagines the future in order to provide life with temporal continuity and meaning. Instead, Trump has always lived in the emotionally vivid moment (episode), fighting to win each moment, moment by discrete moment. Seeing him through the lens of the episodic man helps to explain many puzzling features of Donald Trump’s personality, from his charismatic effect on millions of Americans to his penchant for lying and malice. Importantly, the analysis of Trump’s episodic nature informs the scientific study of narrative identity and meaning making more generally, suggesting that people vary not only with respect to the kinds of stories they create for their lives but also with respect to the extent to which they construe life in narrative terms. Therefore, the analysis of Trump illustrates the potentially reciprocal relationship between the idiographic case and the nomothetic effort to develop and evaluate more general scientific hypotheses.

Eleven Namibian rains: A phenomenological analysis of experience in time

The Damara pastoralists ( ǂnūkhoen) in Namibia distinguish a diverse range of rains. Some rains kill livestock, others care for insects and still others wash away the footprints of the deceased, allowing the person to exist in the spirit realm. While anthropologists have documented cultural classifications like the Namibian rains for decades, we still lack a convincing theory to explain how they come to exist. To address this, I develop a phenomenological perspective and theorise how experience contributes to what rain becomes. I argue with Husserl that the present in which we experience the rain is not a discrete moment, but a unity across a succession of ‘nows’. In the process, perceptions, images, memories and expectations about past and future events blend. In other words, a web of meaningful relationships connects the rain we experience ‘now’ with multiple past and future entities, including people, plants, spirits and animals. I refer to this as network formation. Combining the analyses of the people's pastoral being-in-the-world and their historical–political context, including post-colonialism, allows an explanation as to why some of those combinations are singled out and become distinct ontological entities. I refer to this as node selection. Combining the two processes – network formation and node selection – allows for an explanation as to why precipitation becomes discernible and meaningful as eleven different Namibian rains.

The Erotics of Urbanity

In the Conclusion, I draw on the analytical purchase of eroticism to provide a distinct vantage point onto the connections between urbanity, friendship, and spirituality. Adopting a different way of doing history in the field of early modern Persianate studies, I focus on a discrete moment in the story of Isfahan to think more broadly with historians of sexuality about the valences of erotic desires that bound together networks of friends living in previous centuries. Thinking sex with the early moderns compels me to see erasures that today silence passionate friendships and obscures the entangled history that love shared with eros and beauty. My history of Isfahan presents an early emergence of heteroerotic anxieties, provoked by the adab of urban love and Sufi homoerotic desire, that in the twentieth century were recuperated to make Iran modern.

Laboratory versus daily life gait characteristics in patients with multiple sclerosis, Parkinson’s disease, and matched controls

Background and purpose Recent findings suggest that a gait assessment at a discrete moment in a clinic or laboratory setting may not reflect functional, everyday mobility. As a step towards better understanding gait during daily life in neurological populations, we compared gait measures that best discriminated people with multiple sclerosis (MS) and people with Parkinson’s Disease (PD) from their respective, age-matched, healthy control subjects (MS-Ctl, PD-Ctl) in laboratory tests versus a week of daily life monitoring. Methods We recruited 15 people with MS (age mean ± SD: 49 ± 10 years), 16 MS-Ctl (45 ± 11 years), 16 people with idiopathic PD (71 ± 5 years), and 15 PD-Ctl (69 ± 7 years). Subjects wore 3 inertial sensors (one each foot and lower back) in the laboratory followed by 7 days during daily life. Mann–Whitney U test and area under the curve (AUC) compared differences between PD and PD-Ctl, and between MS and MS-Ctl in the laboratory and in daily life. Results Participants wore sensors for 60–68 h in daily life. Measures that best discriminated gait characteristics in people with MS and PD from their respective control groups were different between the laboratory gait test and a week of daily life. Specifically, the toe-off angle best discriminated MS versus MS-Ctl in the laboratory (AUC [95% CI] = 0.80 [0.63–0.96]) whereas gait speed in daily life (AUC = 0.84 [0.69–1.00]). In contrast, the lumbar coronal range of motion best discriminated PD versus PD-Ctl in the laboratory (AUC = 0.78 [0.59–0.96]) whereas foot-strike angle in daily life (AUC = 0.84 [0.70–0.98]). AUCs were larger in daily life compared to the laboratory. Conclusions Larger AUC for daily life gait measures compared to the laboratory gait measures suggest that daily life monitoring may be more sensitive to impairments from neurological disease, but each neurological disease may require different gait outcome measures.

The Discrete Moment Problem with Nonconvex Shape Constraints

The discrete moment problem aims to find a worst-case discrete distribution that satisfies a given set of moments. This paper studies the discrete moment problems with additional shape constraints that guarantee the worst-case distribution is either log-concave (LC) or has an increasing failure rate (IFR) or increasing generalized failure rate (IGFR). These classes are useful in practice, with applications in revenue management, reliability, and inventory control. The authors characterize the structure of optimal extreme point distributions and show, for example, that an optimal extreme point solution to a moment problem with m moments and LC shape constraints is piecewise geometric with at most m pieces. Using this optimality structure, they design an exact algorithm for computing optimal solutions in a low-dimensional space of parameters. The authors leverage this structure to study a robust newsvendor problem with shape constraints and compute optimal solutions.

Optimization of Velocity Mode in Buslaev Two-Contour Networks via Competition Resolution Rules

<p>In computer networks based on the principle of packet switching, the important transmitting function is to maintain packet queues and suppress congestion. Therefore, the problems of optimal control of the communication networks are relevant. For example, there are users, and no more than a demand of one user can be served simultaneously. This paper considers a discrete dynamical system with two contours and two common points of the contours called the <em>nodes</em>. There are <em>n</em> cells and particles, located in the cells. At any discrete moment the particles of each contour occupy neighboring cells and form a cluster. The nodes divide each contour into two parts of length and (non-symmetrical system). The particles move in accordance with rule of the elementary cellular automaton 240 in the Wolfram classification. Delays in the particle movement are due to that more than one particle cannot move through the node simultaneously. A competition (conflict) occurs when two clusters come to the same node simultaneously. We have proved that the spectrum of velocities contains no more than two values for any fixed <em>n , d</em> and <em>l</em>. We have found an optimal rule which minimizes the average velocity of clusters. One of the competition clusters passes through the node first in accordance with a given competition rule. Two competition resolutions rules are introduced. The rules are called input priority and output priority resolution rules. These rules are Markovian, i.e., they takes into account only the present state of the system. For each set of parameters <em>n, d</em> and <em>l</em>, one of these two rules is optimal, i.e., this rule maximizes the average velocity of clusters. These rules are compared with the left-priority resolution rule, which was considered earlier. We have proved that the spectrum of velocities contains no more two values for any fixed <em>n, l,</em> and <em>d</em>. We have proved that the input priority rule is optimal if , and the output priority rule is optimal if .</p>

Prologue

The prologue introduces this psychological interpretation of Donald Trump’s life through the lens of Robert Louis Stevenson’s 19th-century novel, The Strange Case of Dr. Jekyll and Mr. Hyde. Whereas Stevenson’s story famously illustrated the split duality of human personality, the strange case of Donald Trump suggests a startling reversal: There is no duality: Trump is all Hyde, and no Jekyll. In the strange case of Donald Trump, there is no artifice, no hidden inner self behind the public persona. Trump is completely present in the moment, which is the psychological key to understanding his overwhelming strangeness. He is a man without an inner story, a primal force that moves from one discrete moment in life to the next, with no narrative build-up, no story arc. The prologue introduces the book as an evidence-based and objective analysis of Trump’s life and his personality, drawing extensively upon contemporary research and theory in personality, developmental, and social psychology.

A second-order weak approximation of SDEs using a Markov chain without Lévy area simulation

This paper proposes a new Markov chain approach to second-order weak approximations of stochastic differential equations (SDEs) driven by d-dimensional Brownian motion. The scheme is explicitly constructed by polynomials of Brownian motions up to second order, and any discrete moment-matched random variables or the Lévy area simulation method are not used. The required number of random variables is still d in one-step simulation of the implementation of the scheme. In the Markov chain, a correction term with Lie bracket of vector fields associated with SDEs appears as the cost of not using moment-matched random variables.