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According to the American Cancer Society (2020), it is estimated that 1.8 million new cancer diagnoses will occur in 2019 in the United States. Due to the frequency of cancer diagnoses and the increasing costs of treatment, financial stress is common among cancer patients. Guided by the Family Systems Illness Model (FSI), a cross-sectional study of individuals and family members where there was an active cancer diagnosis (n = 53) was conducted. The study utilized structural equation modeling to examine the impact of cancer stress and financial stress on maladaptive family coping mechanisms, and in turn, their effect on family communication and satisfaction. Findings indicate individuals with higher financial stress reported greater cancer stress. In turn, individuals with higher cancer stress, reported higher rigidity in their family coping which was associated with less family satisfaction. Additionally, as individuals reported greater family disengagement and chaos, lower levels of family communication and satisfaction were found. These findings provide evidence to the complex stresses experienced by cancer patients and their families. Therapeutic implications of how emotionally focused therapy may support these families dealing with a cancer diagnosis are discussed. [ABSTRACT FROM AUTHOR]

The deleterious nature of U.S. economic recessions over the last several decades highlight a need to investigate the role of family economic strain on families. The current study explored the impact of family economic strain on marital quality and marital stability through dyadic associations of marital support and work–family conflict of 370 married couples over a 12-year period (1989–2001) through an actor–partner interdependence model, encompassing two major U.S. recessions. Guided by family stress and coping theory, findings are consistent with past research indicating the negative impact of family economic strain on marital quality and marital stability; however, this impact may be mitigated through the mediation of positive perceptions of marital support and work–family conflict. Implications suggest financial counselors should consider the lasting influence of economic strain on families, and how the psychosocial resources of martial support and managing work–family conflict may promote relationship quality and stability. [ABSTRACT FROM AUTHOR]

This paper presents the benefits and potential concerns of integrating financial counseling with systems therapy. Ethical and conceptual issues of cross-disciplinary collaboration are presented. Issues of social inequity and social determinants of health are highlighted to show the need for critical theory and knowledge of economic injustice in order to do cross disciplinary collaboration. Two models: one for cross disciplinary skills implementation and one for professional collaboration are presented. The paper closes with five recommendations for integrating financial therapy and systems theory. [ABSTRACT FROM AUTHOR]

The central claim of this article is that Jonathan Z. Smith, in addition to his extensive contributions to the study of religion, makes a valuable contribution to the theory and responsible public exercise of cognitive power. This larger public concern is explicitly and repeatedly addressed in his writings on the academy in which he develops a theory of the academy that articulates the conditions essential to the responsible exercise of cognitive power. A further claim is that this theory constitutes the integrating standpoint of his study of religion. The failure to recognize the relationship between his theoretical writings on the academy and his study of religion, reflecting his two careers, has given rise to misunderstandings that have obscured the wider public significance of his entire oeuvre. [ABSTRACT FROM AUTHOR]

Motivation: When proteins mutate or bind to ligands, their backbones often move significantly, especially in loop regions. Computational protein design algorithms must model these motions in order to accurately optimize protein stability and binding affinity. However, methods for backbone conformational search in design have been much more limited than for sidechain conformational search. This is especially true for combinatorial protein design algorithms, which aim to search a large sequence space efficiently and thus cannot rely on temporal simulation of each candidate sequence. Results: We alleviate this difficulty with a new parameterization of backbone conformational space, which represents all degrees of freedom of a specified segment of protein chain that maintain valid bonding geometry (by maintaining the original bond lengths and angles and ω dihedrals). In order to search this space, we present an efficient algorithm, CATS, for computing atomic coordinates as a function of our new continuous backbone internal coordinates. CATS generalizes the iMinDEE and EPIC protein design algorithms, which model continuous flexibility in sidechain dihedrals, to model continuous, appropriately localized flexibility in the backbone dihedrals φ and ψ as well. We show using 81 test cases based on 29 different protein structures that CATS finds sequences and conformations that are significantly lower in energy than methods with less or no backbone flexibility do. In particular, we show that CATS can model the viability of an antibody mutation known experimentally to increase affinity, but that appears sterically infeasible when modeled with less or no backbone flexibility. [ABSTRACT FROM AUTHOR]

Practical protein design problems require designing sequences with a combination of affinity, stability, and specificity requirements. Multistate protein design algorithms model multiple structural or binding 'states' of a protein to address these requirements. comets provides a new level of versatile, efficient, and provable multistate design. It provably returns the minimum with respect to sequence of any desired linear combination of the energies of multiple protein states, subject to constraints on other linear combinations. Thus, it can target nearly any combination of affinity (to one or multiple ligands), specificity, and stability (for multiple states if needed). Empirical calculations on 52 protein design problems showed comets is far more efficient than the previous state of the art for provable multistate design (exhaustive search over sequences). comets can handle a very wide range of protein flexibility and can enumerate a gap-free list of the best constraint-satisfying sequences in order of objective function value. [ABSTRACT FROM AUTHOR]

In 1995, a dynamic cadastre, based on a dynamic geodetic datum, was proposed for New Zealand to recognise that all cadastral boundaries are in motion. Subsequently New Zealand implemented a semi-dynamic geodetic datum which is accompanied by a deformation model. In 2010 and 2011, the Canterbury region in the South Island of New Zealand was subjected to a sequence of earthquakes that resulted in some boundaries being ruptured by up to 4 metres. A set of localised deformation models was developed to model the seismic movements. The implementation of these models and their accuracy are addressed in this paper. [ABSTRACT FROM PUBLISHER]

Computational, in silico prediction of resistance-conferring escape mutations could accelerate the design of therapeutics less prone to resistance. This article describes how to use the Resistor algorithm to predict escape mutations. Resistor employs Pareto optimization on four resistance-conferring criteria—positive and negative design, mutational probability, and hotspot cardinality—to assign a Pareto rank to each prospective mutant. It also predicts the mechanism of resistance, that is, whether a mutant ablates binding to a drug, strengthens binding to the endogenous ligand, or a combination of these two factors, and provides structural models of the mutants. Resistor is part of the free and open-source computational protein design software OSPREY. [ABSTRACT FROM AUTHOR]

We present control strategies that implement planar microassembly using groups of stress-engineered MEMS microrobots (MicroStressBots) controlled through a single global control signal. The global control signal couples the motion of the devices, causing the system to be highly underactuated. In order for the robots to assemble into arbitrary planar shapes despite the high degree of underactuation, it is desirable that each robot be independently maneuverable (independently controllable). To achieve independent control, we fabricated robots that behave (move) differently from one another in response to the same global control signal. We harnessed this differentiation to develop assembly control strategies, where the assembly goal is a desired geometric shape that can be obtained by connecting the chassis of individual robots. We derived and experimentally tested assembly plans that command some of the robots to make progress toward the goal, while other robots are constrained to remain in small circular trajectories (orbits) until it is their turn to move into the goal shape.Our control strategies were tested on systems of fabricated MicroStressBots. The robots are 240–280 µm × 60 µm × 7–20 µm in size and move simultaneously within a single operating environment. We demonstrated the feasibility of our control scheme by accurately assembling five different types of planar microstructures. [ABSTRACT FROM AUTHOR]

Abstract: We present new electron microprobe and Sr-isotope analytical results from mixing experiments using natural volcanic samples. In order to constrain the dynamics of such mixing events, we applied a Taylor–Couette flow, simulating forced convection under very low Reynolds numbers, in a time series ranging from 1 h up to 1 week. The end-member melts derive from samples of the Campanian Ignimbrite (CI), in Italy. The CI is thought to represent a layered reservoir formed in 3 stages: 1) a resident phono-trachytic magma reservoir (end-member A); replenished by 2) a less evolved trachybasaltic–trachytic magma (end-member B of trachytic composition); 3) short-term pre-eruptive mixing in the shallow chamber between a new trachytic and the phono-trachytic resident magmas. Our experiments are motivated by this hypothesis. The two end-members are stirred together, under constant low flow velocity (0.5 rotations per minute). This initially generates single convection cells, which cause progressive homogenization of some major components. This is the case after 1, 4 and 9 h. After 16 h the 87Sr/86Sr-isotopic system is homogenized and the starting compositions are fully mixed. Then separate convection cells and compositional layering for major and minor elements emerged. Based on microprobe measurements of quenched melts (glass) from the 16-hour, 25-hour and 1-week long experiments, we confirm the separation of layers having different densities. This phenomenon is locally complicated by the production of micro-volumes of unmixed melts. Our results support the effectiveness of the interplay between convection and diffusion, enhanced by a double-diffusive–convection-driven differentiation for moderately high-silica magmas under high (near-liquidus) temperatures, attesting that differentiation initiates in the liquidus before the onset of fractional crystallization. [Copyright &y& Elsevier]

We present designs, theory, and results of fabrication and testing for a novel parallel microrobotic assembly scheme using stress-engineered MEMS microrobots. The robots are 240-280 μm x 60 μm x 7-20 μm in size and can be controlled to dock compliantly together, forming planar structures several times this size. The devices are classified into species based on the design of their steering arm actuators, and the species are further classified as independent if they can be maneuvered independently using a single global control signal. In this paper, we show that microrobot species are independent if the two transition voltages of their steering arms, i.e., the voltages at which the arms are raised or lowered, form a unique pair. We present control algorithms that can be applied to groups of independent microrobot species to direct their motion from arbitrary nondeadlock configurations to desired planar microassemblies. We present designs and fabrication for four independent microrobot species, each with a unique transition voltage. The fabricated microrobots are used to demonstrate directed assembly of five types of planar structures from two classes of initial conditions. We demonstrate an average docking accuracy of 5 μm and use self-aligning compliant interaction between the microrobots to further align and stabilize the intermediate assemblies. The final assemblies match their target shapes on average 96%, by area. [ABSTRACT FROM AUTHOR]

We present an untethered, electrostatic, MEMS micro-robot, with dimensions of 60 µm by 250 µm by 10 µm. The device consists of a curved, cantilevered steering arm, mounted on an untethered scratch drive actuator (USDA). These two components are fabricated monolithically from the same sheet of conductive polysilicon, and receive a common power and control signal through a capacitive coupling with an underlying electrical grid. All locations on the grid receive the same power and control signal, so that the devices can be operated without knowledge of their position on the substrate. Individual control of the component actuators provides two distinct motion gaits (forward motion and turning), which together allow full coverage of a planar workspace. These MEMS micro-robots demonstrate turning error of less than 3.7°/mm during forward motion, turn with radii as small as 176 µm, and achieve speeds of over 200 µm/sec with an average step size as small as 12 nm. They have been shown to operate open-loop for distances exceeding 35 cm without failure, and can be controlled through teleoperation to navigate complex paths. The devices were fabricated through a multiuser surface micromachining process, and were postprocessed to add a patterned layer of tensile chromium, which curls the steering arms upward. After sacrificial release, the devices were transferred with a vacuum microprobe to the electrical grid for testing. This grid consists of a silicon substrate coated with 13-µm microfabricated electrodes, arranged in an interdigitated fashion with 2-µm spaces. The electrodes are insulated by a layer of electron-beam-evaporated zirconium dioxide, so that devices placed on top of the electrodes will experience an electrostatic force in response to an applied voltage. Control waveforms are broadcast to the device through the capacitive power coupling, and are decoded by the electromechanical response of the device body. Hysteresis in the system allows on-board storage of ii = 2 bits of state information in response to these electrical signals. The presence of on-board state information within the device itself allows each of the two device subsystems (USDA and steering arm) to be individually addressed and controlled. We describe this communication and control strategy and show necessary and sufficient conditions for voltage-selective actuation of all 2n system states, both for our devices (n = 2), and for the more general case (where n is larger.) [ABSTRACT FROM AUTHOR]

Presents a microelectromechanical (MEMS) actuator that operates free of any physically restraining tethers. How a capacitive coupling can be used to deliver power to untethered MEMS devices independently of the latter's position and orientation; Mechanical release process; Postprocessing sequence for a standard MEMS multiproject wafer process; Post hoc addition of a layer of dielectric between two previously deposited polysilicon films.

Proves the existence of devices for parts positioning and orienting that can bring arbitrary parts into exactly one or two stable equilibria. Squeeze fields and radial fields; Conditions for equilibria; Stable equilibrium orientation.

A literature review of peer-reviewed articles published 2000–2019 was conducted to determine the types and extent of hypertension-associated productivity loss among adults in the United States. All monetary outcomes were standardized to 2019 $ by using the Employment Cost Index. Twenty-seven articles met the inclusion criteria. Nearly half of the articles (12 articles) presented monetary outcomes of productivity loss. Absenteeism (14 articles) and presenteeism (8 articles) were most frequently assessed. Annual absenteeism was estimated to cost more than $11 billion, nationally controlling for sociodemographic characteristics. The annual additional costs per person were estimated at $63 for short-term disability, $72–$330 for absenteeism, and $53–$156 for presenteeism, controlling for participant characteristics; and may be as high as $2362 for absenteeism and presenteeism when considered in combination. The annual additional time loss per person was estimated as 1.3 days for absenteeism, controlling for common hypertension comorbidities, including stroke and diabetes; and 15.6 days for work and home productivity loss combined, controlling for sociodemographic characteristics. The loss from absenteeism alone might be more than 20% of the total medical expenditure of hypertension. Although the differences in estimation methods and study populations make it challenging to synthesize the costs across the studies, this review provides detailed information on the various types of productivity loss. In addition, the ways in which methods could be standardized for future research are discussed. Accounting for the costs from productivity loss can help public health officials, health insurers, employers, and researchers better understand the economic burden of hypertension. [ABSTRACT FROM AUTHOR]

Scanning calorimetric determination of the glass transition temperatures (Tg) of sodium disilicate doped individually with 25 wt.% of the oxides of La, Ce, Pr, Nd, Sm, Eu, Gd, Tb, Dy, Ho, Er, Tm, Yb, and Lu reveals the presence of the so‐called "lanthanide tetrad effect" in their glass transition temperatures. This is to the best of our knowledge the first observation of a tetrad effect in the macroscopic properties of a high‐temperature silicate phase. [ABSTRACT FROM AUTHOR]

Analyzes information invariants for distributed manipulation. Use of cooperating mobile robots for manipulation experiments; Protocols described in the experiment; Situated sensor systems; Manipulation circuits; Comparison of protocols using reductions; Computation of reductions.

We consider the problem of planning and predicting the motion of a flexible object amid obstacles in the plane. We model the flexible object as a rigid "root" body attached to compliant members by torsional springs. The root's position may be controlled, but the compliant members move in response to forces from contact with the environment. Such a model encompasses several important and complicated mechanisms in mechanical design and automated assembly: snap-fasteners, latches, ratchet-and-pawl mechanisms, and escapements. The problem is to predict the motion of such a mechanism amid fixed obstacles. For example, our algorithm could be used to determine whether a snap-fastener design can be assembled with a certain plan. In this article we analyze the physics of these flexible devices and develop combinatorially precise algorithms for predicting their movement under a motion plan. Our algorithms determine when and where the motion will terminate and also. compute the time history of contacts and mating forces. In addition to providing the first known exact algorithm that addresses flexibility in motion planning, we also note that our approach to compliance permits an exact algorithm for predicting motions under rotational compliance, which was not possible in earlier work. We discuss the following issues: the relevance of our approach to engineering (which we illustrate through examples we ran using our system), the computational methods employed, the algebraic techniques for predicting motions in contact with rotational compliance, and issues of robustness and stability of our geometric and algebraic algorithms. Our computational viewpoint lies in the interface between differential theories of mechanics and combinatorial collision detection algorithms. From this viewpoint, subtle mathematical difficulties arise' in predicting motions under rotational compliance, such as the forced nongenericity of the intersection problems encountered in configuration spa... [ABSTRACT FROM AUTHOR]

Robots must plan and execute tasks in the presence of uncertainty. Uncertainty arises from sensing errors, control errors, and the geometry of the environment. By employing a combined strategy of force and position control, a robot programmer can often guarantee reaching the desired final configuration from all the likely initial configurations. Such motion strategies permit robots to carry out tasks in the presence of significant uncertainty. However, compliant motion strategies are very difficult for humans to specify. For this reason we have been working on the automatic synthesis of motion strategies for robots. In previous work (Donald 1988b; 1989), we presented a framework for computing one-step motion strategies that are guaranteed to succeed in the presence of all three kinds of uncertainty. The motion strategies comprise sensor-based gross motions, compliant motions, and simple pushing motions. However, it is not always possible to find plans that are guaranteed to succeed. For example, if tolerancing errors render an assembly infeasible, the plan executor should stop and signal failure. In such cases the insistence on guaranteed success is too restrictive. For this reason we investigate error detection and recovery (EDR) strategies. EDR plans will succeed or fail recognizably: in these more general strategies, there is no possibility that the plan will fail without the executor realizing it. The EDR framework fills a gap when guaranteed plans cannot be found or do not exist; it provides a technology for constructing plans that might work, but fail in a "reasonable" way when they cannot. We describe techniques for planning multi-step EDR strategies in the presence of uncertainty. Multi-step strategies are considerably more difficult to generate, and we introduce three approaches for their synthesis: these are the Push-forward Algorithm, Failure Mode Analysis, and the Weak EDR Theory. We have implemented the theory in the form of a planner, called ... [ABSTRACT FROM AUTHOR]

Background: There is a dearth of studies assessing non-communicable disease (NCD) mortality within population-based settings in Uganda. We assessed mortality due to major NCDs among persons ≥ 30 years in Eastern Uganda from 2010 to 2016. Methods: The study was carried out at the Iganga-Mayuge health and demographic surveillance site in the Iganga and Mayuge districts of Eastern Uganda. Information on cause of death was obtained through verbal autopsies using a structured questionnaire to conduct face-face interviews with carers or close relatives of the deceased. Physicians assigned likely cause of death using ICD-10 codes. Age-adjusted mortality rates were calculated using direct method, with the average population across the seven years of the study (2010 to 2016) as the standard. Age categories of 30–40, 41–50, 51–60, 61–70, and ≥ 71 years were used for standardization. Results: A total of 1,210 deaths among persons ≥ 30 years old were reported from 2010 to 2016 (50.7% among women). Approximately 53% of all deaths were due to non-communicable diseases, 31.8% due to communicable diseases, 8.2% due to injuries, and 7% due to maternal-related deaths or undetermined causes. Cardiovascular diseases accounted for the largest proportion of NCD deaths in each year, and women had substantially higher cardiovascular disease mortality rates compared to men. Conversely, women had lower diabetes mortality rates than men for five of the seven years examined. Conclusions: Non-communicable diseases are major causes of death among adults in Iganga and Mayuge; and cardiovascular diseases and diabetes are leading causes of NCD deaths. Efforts are needed to tackle NCD risk factors and provide NCD care to reduce associated burden and premature mortality. [ABSTRACT FROM AUTHOR]

Background: Efforts aimed at reducing morbidity and mortality associated with pneumonia in children aged five years and below largely depend on caretakers. This study aimed to assess the factors associated with knowledge, attitudes, and practices of caretakers regarding pneumonia. Methods: This was a cross-sectional study carried out within Iganga and Mayuge health and demographic surveillance site (IMHDSS) cohort in Eastern Uganda. Caretakers of children under the age of five years were assessed for knowledge, attitudes, and practices using a set of indicators. The caretaker characteristics as determinants for knowledge, attitude, and practices in relation to pneumonia management were assessed for association. Logistic regression was used to assess the factors associated with caretaker knowledge, attitudes and practices. Results: A total of 649 caretakers of children five years and below of age were interviewed. Caretakers knew pneumonia as one of the childhood diseases, but were less knowledgeable about its transmission, signs and symptoms, risk factors and treatment. Overall, 28% had good knowledge, 36% had moderate knowledge and 35% had poor knowledge. The caretaker attitude was good for more than a half of the respondents (57%), while majority reported good practices (74.1%). Older age (OR = 1.63, 95% CI (1.05–2.51)), Tertiary education (OR = 4.92, 95% CI (2.5–9.65)), being married (OR = 1.82, 95% CI (1.05–3.15)) were associated with having good knowledge. Age above 35 years (aOR = 1.48, 95% CI (1.03–2.11)), and main source of livelihood were associated with good attitude and lastly being female (OR = 2.3, 95% CI (1.23–4.37)), being a Muslim (aOR = 0.5, 95% CI (0.35–0.75)), and being a farmer (OR = 0.5, 95% CI (0.33–0.85)) were associated with being a good caretaker practice. Conclusions: The caretakers of children five years and below, have relatively adequate knowledge about the signs and symptoms of pneumonia, risk factors and treatment measures. Higher education, being married, and being a salary earner were associated with better knowledge about pneumonia, while being female, being a Muslim, and being a peasant farmer were associated with good practice. Targeted interventions to equip caretakers with relevant and adequate skills and knowledge for lower-income and less educated caretakers, considering cultural and religious beliefs about childhood pneumonia identification and management are required. [ABSTRACT FROM AUTHOR]

Background: The disconnect between research and clinical practice leads to research evidence that is often not useful for clinical practice. Practice-based research networks are collaborations between researchers and clinicians aimed at coproducing more useful research. Such networks are rare in the physiotherapy field. We aimed to describe (i) clinicians' motivations behind, and enablers to, participating in a network, (ii) the process of network establishment and (iii) research priorities for a practice-based network of physiotherapists in the Hunter Region of New South Wales (NSW), Australia that supports research coproduction. Methods: We describe the methods and outcomes of the three steps we used to establish the network. Step 1 involved consultation with local opinion leaders and a formative evaluation to understand clinicians' motivations behind, and enablers to, participating in a network. Step 2 involved establishment activities to generate a founding membership group and codesign a governance model. Step 3 involved mapping clinical problems through a workshop guided by systems thinking theory with local stakeholders and prioritizing research areas. Results: Through formative evaluation focus groups, we generated five key motivating themes and three key enablers for physiotherapists' involvement in the network. Establishment activities led to a founding membership group (n = 29, 67% from private practice clinics), a network vision and mission statement, and a joint governance group (9/13 [70%] are private practice clinicians). Our problem-mapping and prioritization process led to three clinically relevant priority research areas with the potential for significant change in practice and patient outcomes. Conclusions: Clinicians are motivated to break down traditional siloed research generation and collaborate with researchers to solve a wide array of issues with the delivery of care. Practice-based research networks have promise for both researchers and clinicians in the common goal of improving patient outcomes. [ABSTRACT FROM AUTHOR]

Abstract Nuclear Magnetic Resonance (NMR) experiments provide distances between nearby atoms of a protein molecule. The corresponding structure determination problem is to determine the 3D protein structure by exploiting such distances. We present a new order on the atoms of the protein, based on information from the chemistry of proteins and NMR experiments, which allows us to formulate the problem as a combinatorial search. Additionally, this order tells us what kind of NMR distance information is crucial to understand the cardinality of the solution set of the problem and its computational complexity. [ABSTRACT FROM AUTHOR]

Computational protein design (CPD) algorithms that compute binding affinity, Ka, search for sequences with an energetically favorable free energy of binding. Recent work shows that three principles improve the biological accuracy of CPD: ensemble-based design , continuous flexibility of backbone and side-chain conformations, and provable guarantees of accuracy with respect to the input. However, previous methods that use all three design principles are single-sequence (SS) algorithms, which are very costly: linear in the number of sequences and thus exponential in the number of simultaneously mutable residues. To address this computational challenge, we introduce BBK* , a new CPD algorithm whose key innovation is the multisequence (MS) bound: BBK* efficiently computes a single provable upper bound to approximate Ka for a combinatorial number of sequences , and avoids SS computation for all provably suboptimal sequences. Thus, to our knowledge, BBK* is the first provable, ensemble-based CPD algorithm to run in time sublinear in the number of sequences. Computational experiments on 204 protein design problems show that BBK* finds the tightest binding sequences while approximating Ka for up to 105-fold fewer sequences than the previous state-of-the-art algorithms, which require exhaustive enumeration of sequences. Furthermore, for 51 protein–ligand design problems, BBK* provably approximates Ka up to 1982-fold faster than the previous state-of-the-art iMinDEE/ \documentclass{aastex}\usepackage{amsbsy}\usepackage{amsfonts}\usepackage{amssymb}\usepackage{bm}\usepackage{mathrsfs}\usepackage{pifont}\usepackage{stmaryrd}\usepackage{textcomp}\usepackage{portland, xspace}\usepackage{amsmath, amsxtra}\usepackage{upgreek}\pagestyle{empty}\DeclareMathSizes{10}{9}{7}{6}\begin{document} $${\curr A^*}$$ \end{document} / \documentclass{aastex}\usepackage{amsbsy}\usepackage{amsfonts}\usepackage{amssymb}\usepackage{bm}\usepackage{mathrsfs}\usepackage{pifont}\usepackage{stmaryrd}\usepackage{textcomp}\usepackage{portland, xspace}\usepackage{amsmath, amsxtra}\usepackage{upgreek}\pagestyle{empty}\DeclareMathSizes{10}{9}{7}{6}\begin{document} $${\curr K^*}$$ \end{document} algorithm. Therefore, BBK* not only accelerates protein designs that are possible with previous provable algorithms, but also efficiently performs designs that are too large for previous methods. [ABSTRACT FROM AUTHOR]

Background: Physiotherapists deliver evidence-based guideline recommended treatments only half of the time to patients with musculoskeletal conditions. Physiotherapists' behaviour in clinical practice are influenced by many cognitive, social, and environmental factors including time and financial pressures. Many initiatives aimed at improving physiotherapists' uptake of evidence-based care have failed to appreciate the context involved in clinical decisions and clinical practice. Therefore, we aimed to describe: i) opinions toward evidence; ii) how evidence is accessed; iii) factors influencing evidence access; iv) factors influencing evidence application, for physiotherapists working in regional areas.Methods: We used a mixed-methods study with online survey and focus groups. We included registered physiotherapists in the survey and physiotherapists practising in regional New South Wales in the focus groups. Quantitative and qualitative data were used to inform all research objectives. We used eight domains of the Transtheoretical Domains Framework to design survey questions. We analysed quantitative and qualitative data in parallel, then integrated both sources through by developing a matrix while considering the Transtheoretical Domains Framework domains to generate themes.Results: Fifty-seven physiotherapists participated in the study (survey only n = 41; focus group only n = 8; both survey and focus group n = 8). Participants reported that evidence was important, but they also considered patient expectations, colleagues' treatment choices, and business demands in clinical decision making. Physiotherapists reported they access evidence on average 30 minutes or less per week. Competing demands like business administration tasks are barriers to accessing evidence. Participants reported that patient expectations were a major barrier to applying evidence in practice. Environmental and systemic factors, like funding structures or incentives for evidence-based care, and social factors, like lacking or having a culture of accountability and mentorship, were reported as both barriers and enablers to evidence application.Conclusions: This study provides context to physiotherapists' opinion, access, and application of evidence in clinical practice. Physiotherapists' provision of evidence-based care may be improved by enhancing structural support from workplaces to access and apply evidence and exploring discrepancies between physiotherapists' perceptions of patient expectations and actual patient expectations. [ABSTRACT FROM AUTHOR]

Presents the speech made by the author, on his acceptance of the 1996 Mineralogical Society of America Award.

Most protein design algorithms search over discrete conformations and an energy function that is residue-pairwise, that is, a sum of terms that depend on the sequence and conformation of at most two residues. Although modeling of continuous flexibility and of non-residue-pairwise energies significantly increases the accuracy of protein design, previous methods to model these phenomena add a significant asymptotic cost to design calculations. We now remove this cost by modeling continuous flexibility and non-residue-pairwise energies in a form suitable for direct input to highly efficient, discrete combinatorial optimization algorithms such as DEE/A* or branch-width minimization. Our novel algorithm performs a local unpruned tuple expansion (LUTE), which can efficiently represent both continuous flexibility and general, possibly nonpairwise energy functions to an arbitrary level of accuracy using a discrete energy matrix. We show using 47 design calculation test cases that LUTE provides a dramatic speedup in both single-state and multistate continuously flexible designs. [ABSTRACT FROM AUTHOR]

Computational structure-based protein design programs are becoming an increasingly important tool in molecular biology. These programs compute protein sequences that are predicted to fold to a target structure and perform a desired function. The success of a program's predictions largely relies on two components: first, the input biophysical model, and second, the algorithm that computes the best sequence(s) and structure(s) according to the biophysical model. Improving both the model and the algorithm in tandem is essential to improving the success rate of current programs, and here we review recent developments in algorithms for protein design, emphasizing how novel algorithms enable the use of more accurate biophysical models. We conclude with a list of algorithmic challenges in computational protein design that we believe will be especially important for the design of therapeutic proteins and protein assemblies. [ABSTRACT FROM AUTHOR]

Introduces the special issue of the 'International Journal of Robotics Research,' on the Fourth International Workshop on Algorithmic Foundations of Robotics (WAFR). Background information on robot algorithms; Workshop highlights; Program committee members; Topics reported at WAFR 2000.

Antimicrobial resistance presents a significant health care crisis. The mutation F98Y in Staphylococcus aureus dihydrofolate reductase (SaDHFR) confers resistance to the clinically important antifolate trimethoprim (TMP). Propargyl-linked antifolates (PLAs), next generation DHFR inhibitors, are much more resilient than TMP against this F98Y variant, yet this F98Y substitution still reduces efficacy of these agents. Surprisingly, differences in the enantiomeric configuration at the stereogenic center of PLAs influence the isomeric state of the NADPH cofactor. To understand the molecular basis of F98Y-mediated resistance and how PLAs' inhibition drives NADPH isomeric states, we used protein design algorithms in the osprey protein design software suite to analyze a comprehensive suite of structural, biophysical, biochemical, and computational data. Here, we present a model showing how F98Y SaDHFR exploits a different anomeric configuration of NADPH to evade certain PLAs' inhibition, while other PLAs remain unaffected by this resistance mechanism. Author summary: Antimicrobial resistance is a major healthcare crisis. While we were developing novel enzyme inhibitors to combat methicillin-resistant Staphylococcus aureus (MRSA), we found that the chirality of both inhibitor and cofactor can have a large influence on inhibitor potency. Our detailed study of enantiomeric propargyl-linked antifolates (PLAs) shows that the chiral state of inhibitors can affect the chiral state of the cofactor. Moreover, the bacterial enzyme target can exploit cooperative chirality to evade inhibitor binding. We call this phenomenon chiral evasion. Using crystal structures, biochemical assays, computational protein design algorithms, and statistical mechanics, a detailed mechanism for chiral evasion is proposed. While the concept that different enantiomers have different biology is well known, MRSA is unique: we do not know of any other cases where a single mutation (F98Y) flips the chirality preference for cofactor binding and induces stereospecificity for drug binding. Thus, we illuminate the effect of this clinically relevant resistance mutation on the obligate cofactor binding site. These new insights will be useful to develop more durable antibiotics that are resilient to resistance. [ABSTRACT FROM AUTHOR]

Background: This paper describes the statistical analysis plan for a randomised controlled trial of a Healthy Lifestyle Program (HeLP) for low back pain targeting multiple health risks and behaviours, weight, physical activity, diet and smoking, to improve disability. We describe the methods for the main analyses and economic analysis of the trial.Methods and Design: The trial is a two-arm pragmatic randomised controlled trial comparing the effect of the HeLP intervention to usual care on low back pain disability at 26 weeks. A total of 346 adults with low back pain were recruited from the Newcastle and Hunter region between September 2017 and November 2019 and randomised to either HeLP or usual care. HeLP is a 6-month intervention with participant outcomes measured at weeks 6, 12, 26 and 52 post randomisation. This statistical analysis plan describes data integrity, handling and preparation of data for analyses and methods for analyses. The primary endpoint for the trial is disability at 26 weeks using the 24-item self-report Roland Morris Disability Questionnaire. The primary analysis will follow the intention-to-treat principle using linear mixed regression models.Discussion: The statistical analysis plan for this trial was produced to reduce outcome reporting bias arising from knowledge of the study findings. Any deviations will be described and justified in the final report.Trial Registration: Australian New Zealand Clinical Trials Registry ACTRN12617001288314 . Registered on 6 September 2017. [ABSTRACT FROM AUTHOR]

Optimizing amino acid conformation and identity is a central problem in computational protein design. Protein design algorithms must allow realistic protein flexibility to occur during this optimization, or they may fail to find the best sequence with the lowest energy. Most design algorithms implement side-chain flexibility by allowing the side chains to move between a small set of discrete, low-energy states, which we call rigid rotamers. In this work we show that allowing continuous side-chain flexibility (which we call continuous rotamers) greatly improves protein flexibility modeling. We present a large-scale study that compares the sequences and best energy conformations in 69 protein-core redesigns using a rigid-rotamer model versus a continuous-rotamer model. We show that in nearly all of our redesigns the sequence found by the continuous-rotamer model is different and has a lower energy than the one found by the rigid-rotamer model. Moreover, the sequences found by the continuous-rotamer model are more similar to the native sequences. We then show that the seemingly easy solution of sampling more rigid rotamers within the continuous region is not a practical alternative to a continuous-rotamer model: at computationally feasible resolutions, using more rigid rotamers was never better than a continuous-rotamer model and almost always resulted in higher energies. Finally, we present a new protein design algorithm based on the dead-end elimination (DEE) algorithm, which we call iMinDEE, that makes the use of continuous rotamers feasible in larger systems. iMinDEE guarantees finding the optimal answer while pruning the search space with close to the same efficiency of DEE. Availability: Software is available under the Lesser GNU Public License v3. Contact the authors for source code [ABSTRACT FROM AUTHOR]

Abstract: Magma mixing tests have been performed experimentally in a Taylor–Couette-like experimental setting. The variation of trace element concentrations along transects crossing the resultant melt column has been measured. Results indicate a strongly variable mobility of the different trace elements in the same mixing system. Such a different behaviour of trace elements tends to be enhanced as the mixing time increases, leading to the production of highly heterogeneous volumes of melts in which depletion and enrichment of trace elements occurred depending on their potential of spreading across the magma mixing system. The results presented here offer new insights into the complexity of processes expected to be operating during mixing of magmas. It is demonstrated that on short mixing times also the trace elements may become highly non-correlated. This is due to the development of chaotic advection/diffusion processes in the system. These results indicate that the onset of diffusive fractionation processes may strongly influence the patterns of data on inter-elemental diagrams depending on the relative mobility of the different elements. [Copyright &y& Elsevier]

One of the main challenges for protein redesign is the efficient evaluation of a combinatorial number of candidate structures. The modeling of protein flexibility, typically by using a rotamer library of commonly-observed low-energy side-chain conformations, further increases the complexity of the redesign problem. A dominant algorithm for protein redesign is dead-end elimination (DEE), which prunes the majority of candidate conformations by eliminating rigid rotamers that provably are not part of the global minimum energy conformation (GMEC). The identified GMEC consists of rigid rotamers (i.e., rotamers that have not been energy-minimized) and is thus referred to as the rigid-GMEC. As a postprocessing step, the conformations that survive DEE may be energy-minimized. When energy minimization is performed after pruning with DEE, the combined protein design process becomes heuristic, and is no longer provably accurate: a conformation that is pruned using rigid-rotamer energies may subsequently minimize to a lower energy than the rigid-GMEC. That is, the rigid-GMEC and the conformation with the lowest energy among all energy-minimized conformations (the minimized-GMEC) are likely to be different. While the traditional DEE algorithm succeeds in not pruning rotamers that are part of the rigid-GMEC, it makes no guarantees regarding the identification of the minimized-GMEC. In this paper we derive a novel, provable, and efficient DEE-like algorithm, called minimized-DEE (MinDEE), that guarantees that rotamers belonging to the minimized-GMEC will not be pruned, while still pruning a combinatorial number of conformations. We show that MinDEE is useful not only in identifying the minimized-GMEC, but also as a filter in an ensemble-based scoring and search algorithm for protein redesign that exploits energy-minimized conformations. We compare our results both to our previous computational predictions of protein designs and to biological activity assays of predicted protein mutants. Our provable and efficient minimized-DEE algorithm is applicable in protein redesign, protein-ligand binding prediction, and computer-aided drug design. © 2008 Wiley Periodicals, Inc. J Comput Chem, 2008 [ABSTRACT FROM AUTHOR]

High-throughput nuclear magnetic resonance (NMR) structural bi- ology and NMR structural genomics pose a fascinating set of geometric challenges. A key bottleneck in NMR structural biology is the resonance assignment problem. We seek to accelerate protein NMR resonance assignment and structure determination by exploiting a priori structural information, in particularly a method known as nuclear vector replacement (NVR) has been proposed as a method for solving the assignment problem given a priori structural information. Among several different types of input data, NVR uses a particular type of NMR data known as residual dipolar couplings (RDCs). The basic physics of RDCs tells us that the data should be explainable by a structural model and set of parameters contained within the "Saupe alignment tensor". in the NVR algorithm, one estimates the Saupe alignment tensors and then proceeds to refine those estimates. We would like to quantity the accuracy of such estimates, where we compare the estimated Saupe matrix to the correct Saupe matrix. In this work, we propose a way to quantify this comparison. Given a correct Saupe matrix and an estimated Saupe matrix, we compute an upper bound on the probability that a randomly rotated Saupe tensor would have an error smaller than the estimated Saupe matrix. This has the advantage of being a quantified upper bound, which also has a clear interpretation in terms of geometry and probability. While the specific application of our rotation probability results is given to NVR, our novel methods can be used for any RDC-based algorithm to bound the accuracy of the estimated alignment tensors. Furthermore, they could also be used in X-ray crystallography or molecular docking to quantitate the accuracy of calculated rotations of proteins, protein domains, nucleic acids, or small molecules. [ABSTRACT FROM AUTHOR]

The K* algorithm provably approximates partition functions for a set of states (e.g., protein, ligand, and protein-ligand complex) to a user-specified accuracy ε. Often, reaching an ε-approximation for a particular set of partition functions takes a prohibitive amount of time and space. To alleviate some of this cost, we introduce two new algorithms into the osprey suite for protein design: fries, a Fast Removal of Inadequately Energied Sequences, and EWAK*, an Energy Window Approximation to K*. fries pre-processes the sequence space to limit a design to only the most stable, energetically favorable sequence possibilities. EWAK* then takes this pruned sequence space as input and, using a user-specified energy window, calculates K* scores using the lowest energy conformations. We expect fries/EWAK* to be most useful in cases where there are many unstable sequences in the design sequence space and when users are satisfied with enumerating the low-energy ensemble of conformations. In combination, these algorithms provably retain calculational accuracy while limiting the input sequence space and the conformations included in each partition function calculation to only the most energetically favorable, effectively reducing runtime while still enriching for desirable sequences. This combined approach led to significant speed-ups compared to the previous state-of-the-art multi-sequence algorithm, BBK*, while maintaining its efficiency and accuracy, which we show across 40 different protein systems and a total of 2,826 protein design problems. Additionally, as a proof of concept, we used these new algorithms to redesign the protein-protein interface (PPI) of the c-Raf-RBD:KRas complex. The Ras-binding domain of the protein kinase c-Raf (c-Raf-RBD) is the tightest known binder of KRas, a protein implicated in difficult-to-treat cancers. fries/EWAK* accurately retrospectively predicted the effect of 41 different sets of mutations in the PPI of the c-Raf-RBD:KRas complex. Notably, these mutations include mutations whose effect had previously been incorrectly predicted using other computational methods. Next, we used fries/EWAK* for prospective design and discovered a novel point mutation that improves binding of c-Raf-RBD to KRas in its active, GTP-bound state (KRasGTP). We combined this new mutation with two previously reported mutations (which were highly-ranked by osprey) to create a new variant of c-Raf-RBD, c-Raf-RBD(RKY). fries/EWAK* in osprey computationally predicted that this new variant binds even more tightly than the previous best-binding variant, c-Raf-RBD(RK). We measured the binding affinity of c-Raf-RBD(RKY) using a bio-layer interferometry (BLI) assay, and found that this new variant exhibits single-digit nanomolar affinity for KRasGTP, confirming the computational predictions made with fries/EWAK*. This new variant binds roughly five times more tightly than the previous best known binder and roughly 36 times more tightly than the design starting point (wild-type c-Raf-RBD). This study steps through the advancement and development of computational protein design by presenting theory, new algorithms, accurate retrospective designs, new prospective designs, and biochemical validation. Author summary: Computational structure-based protein design is an innovative tool for redesigning proteins to introduce a particular or novel function. One such function is improving the binding of one protein to another, which can increase our understanding of important protein systems. Herein we introduce two novel, provable algorithms, fries and EWAK*, for more efficient computational structure-based protein design as well as their application to the redesign of the c-Raf-RBD:KRas protein-protein interface. These new algorithms speed-up computational structure-based protein design while maintaining accurate calculations, allowing for larger, previously infeasible protein designs. Additionally, using fries and EWAK* within the osprey suite, we designed the tightest known binder of KRas, a heavily studied cancer target that interacts with a number of different proteins. This previously undiscovered variant of a KRas-binding domain, c-Raf-RBD, has potential to serve as a tool to further probe the protein-protein interface of KRas with its effectors and its discovery alone emphasizes the potential for more successful applications of computational structure-based protein design. [ABSTRACT FROM AUTHOR]

Protein design algorithms that model continuous sidechain flexibility and conformational ensembles better approximate the in vitro and in vivo behavior of proteins. The previous state of the art, iMinDEE-A*-K*, computes provable ɛ-approximations to partition functions of protein states (e.g., bound vs. unbound) by computing provable, admissible pairwise-minimized energy lower bounds on protein conformations, and using the A* enumeration algorithm to return a gap-free list of lowest-energy conformations. iMinDEE-A*-K* runs in time sublinear in the number of conformations, but can be trapped in loosely-bounded, low-energy conformational wells containing many conformations with highly similar energies. That is, iMinDEE-A*-K* is unable to exploit the correlation between protein conformation and energy: similar conformations often have similar energy. We introduce two new concepts that exploit this correlation: Minimization-Aware Enumeration and Recursive K*. We combine these two insights into a novel algorithm, Minimization-Aware Recursive K* (MARK*), which tightens bounds not on single conformations, but instead on distinct regions of the conformation space. We compare the performance of iMinDEE-A*-K* versus MARK* by running the Branch and Bound over K* (BBK*) algorithm, which provably returns sequences in order of decreasing K* score, using either iMinDEE-A*-K* or MARK* to approximate partition functions. We show on 200 design problems that MARK* not only enumerates and minimizes vastly fewer conformations than the previous state of the art, but also runs up to 2 orders of magnitude faster. Finally, we show that MARK* not only efficiently approximates the partition function, but also provably approximates the energy landscape. To our knowledge, MARK* is the first algorithm to do so. We use MARK* to analyze the change in energy landscape of the bound and unbound states of an HIV-1 capsid protein C-terminal domain in complex with a camelid VHH, and measure the change in conformational entropy induced by binding. Thus, MARK* both accelerates existing designs and offers new capabilities not possible with previous algorithms. [ABSTRACT FROM AUTHOR]

In this work, we perform textural analysis on volcanic breccias related to the silicic magmatism in the region of São Marcos (southern Brazil), Paraná Magmatic Province. The breccias are matrix-supported, coarse-grained, poorly sorted with angular to rounded fragments in a fine-grained matrix. Juvenile fragments are dense to pumiceous, massive to banded dacites; lithic fragments were not recognised. The analyses were performed on field photographs. Grain size distribution (GSD) analysis showed maximum fragment sizes between − 8 and − 9.5 ϕ and smallest recognised sizes between − 3 and 1.5 ϕ. Due to the spatial resolution limit of the photographs and the weathered condition of the matrix, the fine fragments from the matrix were not analysed. The GSD fractality could be quantified by a single power law, with low/moderate D values of 1.9–2.3. Vesicle size distribution (VSD) and shape parameters of both fragments and vesicles were also measured. The fragments are typically low vesicularity, with median vesicle area fractions around 5% for all samples, but pumiceous fragments with up to 43% area are found. VSDs exhibit single exponential, concave upwards curves, with vesicles becoming more deformed/complex with increasing size, suggesting a single continuous process of nucleation and growth under low degrees of shear. Regarding the fragments' shape parameters, all samples have high values of solidity which, together with the low-vesicularity of the fragments, suggest brittle fragmentation of poorly vesicular material and the operation of secondary fragmentation processes during transport that round and smooth the clasts. However, field evidence for local conduit systems together with the GSD fractality suggest that these may be proximal deposits, without substantial transport history. Based on a comparison of the deposits' characteristics with several types of volcanic breccias, we propose a block and ash flow source for these breccias that indicate the presence of nearby lava domes, providing evidence for high-viscosity low-flux dacitic volcanism in the Paraná Magmatic Province. [ABSTRACT FROM AUTHOR]

Pyroclastic currents are catastrophic flows of gas and particles triggered by explosive volcanic eruptions. For much of their dynamics, they behave as particulate density currents and share similarities with turbidity currents. Pyroclastic currents occasionally deposit dune bedforms with peculiar lamination patterns, from what is thought to represent the dilute low concentration and fluid‐turbulence supported end member of the pyroclastic currents. This article presents a high resolution dataset of sediment plates (lacquer peels) with several closely spaced lateral profiles representing sections through single pyroclastic bedforms from the August 2006 eruption of Tungurahua (Ecuador). Most of the sedimentary features contain backset bedding and preferential stoss‐face deposition. From the ripple scale (a few centimetres) to the largest dune bedform scale (several metres in length), similar patterns of erosive‐based backset beds are evidenced. Recurrent trains of sub‐vertical truncations on the stoss side of structures reshape and steepen the bedforms. In contrast, sporadic coarse‐grained lenses and lensoidal layers flatten bedforms by filling troughs. The coarsest (clasts up to 10 cm), least sorted and massive structures still exhibit lineation patterns that follow the general backset bedding trend. The stratal architecture exhibits strong lateral variations within tens of centimetres, with very local truncations both in flow‐perpendicular and flow‐parallel directions. This study infers that the sedimentary patterns of bedforms result from four formation mechanisms: (i) differential draping; (ii) slope‐influenced saltation; (iii) truncative bursts; and (iv) granular‐based events. Whereas most of the literature makes a straightforward link between backset bedding and Froude‐supercritical flows, this interpretation is reconsidered here. Indeed, features that would be diagnostic of subcritical dunes, antidunes and 'chute and pools' can be found on the same horizon and in a single bedform, only laterally separated by short distances (tens of centimetres). These data stress the influence of the pulsating and highly turbulent nature of the currents and the possible role of coherent flow structures such as Görtler vortices. Backset bedding is interpreted here as a consequence of a very high sedimentation environment of weak and waning currents that interact with the pre‐existing morphology. Quantification of near‐bed flow velocities is made via comparison with wind tunnel experiments. It is estimated that shear velocities of ca 0·30 m.s−1 (equivalent to pure wind velocity of 6 to 8 m.s−1 at 10 cm above the bed) could emplace the constructive bedsets, whereas the truncative phases would result from bursts with impacting wind velocities of at least 30 to 40 m.s−1. [ABSTRACT FROM AUTHOR]

We present osprey 3.0, a new and greatly improved release of the osprey protein design software. Osprey 3.0 features a convenient new Python interface, which greatly improves its ease of use. It is over two orders of magnitude faster than previous versions of osprey when running the same algorithms on the same hardware. Moreover, osprey 3.0 includes several new algorithms, which introduce substantial speedups as well as improved biophysical modeling. It also includes GPU support, which provides an additional speedup of over an order of magnitude. Like previous versions of osprey, osprey 3.0 offers a unique package of advantages over other design software, including provable design algorithms that account for continuous flexibility during design and model conformational entropy. Finally, we show here empirically that osprey 3.0 accurately predicts the effect of mutations on protein–protein binding. Osprey 3.0 is available at http://www.cs.duke.edu/donaldlab/osprey.php as free and open‐source software. © 2018 Wiley Periodicals, Inc. We present the third major release of the OSPREY protein design software, along with comparisons to experimental data that confirm its ability to optimize protein mutants for desired functions. Osprey 3.0 has significant efficiency, ease‐of‐use, and algorithmic improvements over previous versions, including GPU acceleration and a new Python interface. [ABSTRACT FROM AUTHOR]

The flexibility of biological macromolecules is an important structural determinant of function. Unfortunately, the correlations between different motional modes are poorly captured by discrete ensemble representations. Here, we present new ways to both represent and visualize correlated interdomain motions. Interdomain motions are determined directly from residual dipolar couplings, represented as a continuous conformational distribution, and visualized using the disk-on-sphere representation. Using the disk-on-sphere representation, features of interdomain motions, including correlations, are intuitively visualized. The representation works especially well for multidomain systems with broad conformational distributions.This analysis also can be extended to multiple probability density modes, using a Bingham mixture model. We use this new paradigm to study the interdomain motions of staphylococcal protein A, which is a key virulence factor contributing to the pathogenicity of Staphylococcus aureus . We capture the smooth transitions between important states and demonstrate the utility of continuous distribution functions for computing the reorientational components of binding thermodynamics. Such insights allow for the dissection of the dynamic structural components of functionally important intermolecular interactions. [ABSTRACT FROM AUTHOR]

Protein design algorithms enumerate a combinatorial number of candidate structures to compute the Global Minimum Energy Conformation (GMEC). To efficiently find the GMEC, protein design algorithms must methodically reduce the conformational search space. By applying distance and energy cutoffs, the protein system to be designed can thus be represented using a sparse residue interaction graph, where the number of interacting residue pairs is less than all pairs of mutable residues, and the corresponding GMEC is called the sparse GMEC. However, ignoring some pairwise residue interactions can lead to a change in the energy, conformation, or sequence of the sparse GMEC vs. the original or the full GMEC. Despite the widespread use of sparse residue interaction graphs in protein design, the above mentioned effects of their use have not been previously analyzed. To analyze the costs and benefits of designing with sparse residue interaction graphs, we computed the GMECs for 136 different protein design problems both with and without distance and energy cutoffs, and compared their energies, conformations, and sequences. Our analysis shows that the differences between the GMECs depend critically on whether or not the design includes core, boundary, or surface residues. Moreover, neglecting long-range interactions can alter local interactions and introduce large sequence differences, both of which can result in significant structural and functional changes. Designs on proteins with experimentally measured thermostability show it is beneficial to compute both the full and the sparse GMEC accurately and efficiently. To this end, we show that a provable, ensemble-based algorithm can efficiently compute both GMECs by enumerating a small number of conformations, usually fewer than 1000. This provides a novel way to combine sparse residue interaction graphs with provable, ensemble-based algorithms to reap the benefits of sparse residue interaction graphs while avoiding their potential inaccuracies. [ABSTRACT FROM AUTHOR]

Background Electromagnetic interference (EMI) can affect the function of implantable cardioverter defibrillators (ICD). Hybrid electric vehicles (HEV) have increased popularity and are a potential source of EMI. Little is known about the in vivo effects of EMI generated by HEV on ICD. Objective This study evaluated the in vivo interaction between EMI generated by HEV with ICD. Methods and results Thirty patients (73 ± 9 y/o; 80% male) with stable ICD function were exposed to EMI generated by a Toyota Prius Hybrid®. The vehicle was lifted above the ground, allowing safe changes in engine rotation and consequent variations in electromagnetic emission. EMI was measured (NARDA STS® model EHP-50C) and expressed in A/m (magnetic), Volts/m (electrical), and Hertz (frequency). Six positions were evaluated: driver, front passenger, right and left back seats, outside, at the back and front of the car. Each position was evaluated at idle, 30 mph, 60 mph and variable speeds (acceleration-deceleration-brake). All ICD devices were continuously monitored during the study. The levels of EMI generated were low (highest mean levels: 2.09 A/m at right back seat at 30 mph; and 3.5 V/m at driver seat at variable speeds). No episode of oversensing or inadvertent change in ICD programming was observed. Conclusion It is safe for patients with ICD to interact with HEV. This is the first study to address this issue using an in vivo model. Further studies are necessary to evaluate the interaction of different models of HEV or electric engine with ICD or unipolar pacemakers. [ABSTRACT FROM AUTHOR]

Finding the global minimum energy conformation (GMEC) of a huge combinatorial search space is the key challenge in computational protein design (CPD) problems. Traditional algorithms lack a scalable and efficient distributed design scheme, preventing researchers from taking full advantage of current cloud infrastructures. We design cloud OSPREY (cOSPREY), an extension to a widely used protein design software OSPREY, to allow the original design framework to scale to the commercial cloud infrastructures. We propose several novel designs to integrate both algorithm and system optimizations, such as GMEC-specific pruning, state search partitioning, asynchronous algorithm state sharing, and fault tolerance. We evaluate cOSPREY on three different cloud platforms using different technologies and show that it can solve a number of large-scale protein design problems that have not been possible with previous approaches. [ABSTRACT FROM AUTHOR]

Sparse energy functions that ignore long range interactions between residue pairs are frequently used by protein design algorithms to reduce computational cost. Current dynamic programming algorithms that fully exploit the optimal substructure produced by these energy functions only compute the GMEC. This disproportionately favors the sequence of a single, static conformation and overlooks better binding sequences with multiple low-energy conformations. Provable, ensemble-based algorithms such as A* avoid this problem, but A* cannot guarantee better performance than exhaustive enumeration. We propose a novel, provable, dynamic programming algorithm called Branch-Width Minimization* (BWM*) to enumerate a gap-free ensemble of conformations in order of increasing energy. Given a branch-decomposition of branch-width w for an n-residue protein design with at most q discrete side-chain conformations per residue, BWM* returns the sparse GMEC in O(nw²q3/2w) time and enumerates each additional conformation in merely O(n log q) time. We define a new measure, Total Effective Search Space (TESS), which can be computed efficiently a priori before BWM* or A* is run. We ran BWM* on 67 protein design problems and found that TESS discriminated between BWM*-efficient and A*- efficient cases with 100% accuracy. As predicted by TESS and validated experimentally, BWM* outperforms A* in 73% of the cases and computes the full ensemble or a close approximation faster than A*, enumerating each additional conformation in milliseconds. Unlike A*, the performance of BWM* can be predicted in polynomial time before running the algorithm, which gives protein designers the power to choose the most efficient algorithm for their particular design problem. [ABSTRACT FROM AUTHOR]

One of the main challenges in computational protein design (CPD) is the huge size of the protein sequence and conformational space that has to be computationally explored. Recently, we showed that state-of-the-art combinatorial optimization technologies based on Cost Function Network (CFN) processing allow speeding up provable rigid backbone protein design methods by several orders of magnitudes. Building up on this, we improved and injected CFN technology into the well-established CPD package Osprey to allow all Osprey CPD algorithms to benefit from associated speedups. Because Osprey fundamentally relies on the ability of [ABSTRACT FROM AUTHOR]

Hydrothermal explosions frequently occur in geothermal areas showing various mechanisms and energies of explosivity. Their deposits, though generally hardly recognised or badly preserved, provide important insights to quantify the dynamics and energy of these poorly understood explosive events. Furthermore the host rock lithology of the geothermal system adds a control on the efficiency in the energy release during an explosion. We present results from a detailed study of recent hydrothermal explosion deposits within an active geothermal area at Kverkfjöll, a central volcano at the northern edge of Vatnajökull. On August 15th 2013, a small jökulhlaup occurred when the Gengissig ice-dammed lake drained at Kverkfjöll. The lake level dropped by approximately 30 m, decreasing pressure on the lake bed and triggering several hydrothermal explosions on the 16th. Here, a multidisciplinary approach combining detailed field work, laboratory studies, and models of the energetics of explosions with information on duration and amplitudes of seismic signals, has been used to analyse the mechanisms and characteristics of these hydrothermal explosions. Field and laboratory studies were also carried out to help constrain the sedimentary sequence involved in the event. The explosions lasted for 40–50 s and involved the surficial part of an unconsolidated and hydrothermally altered glacio-lacustrine deposit composed of pyroclasts, lavas, scoriaceous fragments, and fine-grained welded or loosely consolidated aggregates, interbedded with clay-rich levels. Several small fans of ejecta were formed, reaching a distance of 1 km north of the lake and covering an area of approximately 0.3 km 2 , with a maximum thickness of 40 cm at the crater walls. The material (volume of approximately 10 4 m 3 ) has been ejected by the expanding boiling fluid, generated by a pressure failure affecting the surficial geothermal reservoir. The maximum thermal, craterisation and ejection energies, calculated for the explosion areas, are on the order of 10 11 , 10 10 and 10 9 J, respectively. Comparison of these with those estimated by the volume of the ejecta and the crater sizes, yields good agreement. We estimate that approximately 30% of the available thermal energy was converted into mechanical energy during this event. The residual energy was largely dissipated as heat, while only a small portion was converted into seismic energy. Estimation of the amount of freshly-fragmented clasts in the ejected material obtained from SEM morphological analyses, reveals that a low but significant energy consumption by fragmentation occurred. Decompression experiments were performed in the laboratory mimicking the conditions due to the drainage of the lake. Experimental results confirm that only a minor amount of energy is consumed by the creation of new surfaces in fragmentation, whereas most of the fresh fragments derive from the disaggregation of aggregates. Furthermore, ejection velocities of the particles (40–50 m/s), measured via high-speed videos, are consistent with those estimated from the field. The multidisciplinary approach used here to investigate hydrothermal explosions has proven to be a valuable tool which can provide robust constraints on energy release and partitioning for such small-size yet hazardous, steam-explosion events. [ABSTRACT FROM AUTHOR]