Power laws, Pareto distributions and Zipf's law

When the probability of measuring a particular value of some quantity varies inversely as a power of that value, the quantity is said to follow a power law, also known variously as Zipf's law or the Pareto distribution. Power laws appear widely in physics, biology, earth and planetary sciences, economics and finance, computer science, demography and the social sciences. For instance, the distributions of the sizes of cities, earthquakes, solar flares, moon craters, wars and people's personal fortunes all appear to follow power laws. The origin of power-law behaviour has been a topic of debate in the scientific community for more than a century. Here we review some of the empirical evidence for the existence of power-law forms and the theories proposed to explain them.Comment: 28 pages, 16 figures, minor corrections and additions in this versio

Distributed Learning over Unreliable Networks

Most of today's distributed machine learning systems assume {\em reliable networks}: whenever two machines exchange information (e.g., gradients or models), the network should guarantee the delivery of the message. At the same time, recent work exhibits the impressive tolerance of machine learning algorithms to errors or noise arising from relaxed communication or synchronization. In this paper, we connect these two trends, and consider the following question: {\em Can we design machine learning systems that are tolerant to network unreliability during training?} With this motivation, we focus on a theoretical problem of independent interest---given a standard distributed parameter server architecture, if every communication between the worker and the server has a non-zero probability $p$ of being dropped, does there exist an algorithm that still converges, and at what speed? The technical contribution of this paper is a novel theoretical analysis proving that distributed learning over unreliable network can achieve comparable convergence rate to centralized or distributed learning over reliable networks. Further, we prove that the influence of the packet drop rate diminishes with the growth of the number of \textcolor{black}{parameter servers}. We map this theoretical result onto a real-world scenario, training deep neural networks over an unreliable network layer, and conduct network simulation to validate the system improvement by allowing the networks to be unreliable

Do Patients and Oncologists Discuss the Cost of Cancer Treatment? An Observational Study of Clinical Interactions Between African American Patients and Their Oncologists

PURPOSE: Financial toxicity negatively affects patients with cancer, especially racial/ethnic minorities. Patient-oncologist discussions about treatment-related costs may reduce financial toxicity by factoring costs into treatment decisions. This study investigated the frequency and nature of cost discussions during clinical interactions between African American patients and oncologists and examined whether cost discussions were affected by patient sociodemographic characteristics and social support, a known buffer to perceived financial stress. Methods Video recorded patient-oncologist clinical interactions (n = 103) from outpatient clinics of two urban cancer hospitals (including a National Cancer Institute-designated comprehensive cancer center) were analyzed. Coders studied the videos for the presence and duration of cost discussions and then determined the initiator, topic, oncologist response to the patient\u27s concerns, and the patient\u27s reaction to the oncologist\u27s response. RESULTS: Cost discussions occurred in 45% of clinical interactions. Patients initiated 63% of discussions; oncologists initiated 36%. The most frequent topics were concern about time off from work for treatment (initiated by patients) and insurance (initiated by oncologists). Younger patients and patients with more perceived social support satisfaction were more likely to discuss cost. Patient age interacted with amount of social support to affect frequency of cost discussions within interactions. Younger patients with more social support had more cost discussions; older patients with more social support had fewer cost discussions. CONCLUSION: Cost discussions occurred in fewer than one half of the interactions and most commonly focused on the impact of the diagnosis on patients\u27 opportunity costs rather than treatment costs. Implications for ASCO\u27s Value Framework and design of interventions to improve cost discussions are discussed

Turnip mosaic potyvirus probably first spread to Eurasian brassica crops from wild orchids about 1000 years ago

Turnip mosaic potyvirus (TuMV) is probably the most widespread and damaging virus that infects cultivated brassicas worldwide. Previous work has indicated that the virus originated in western Eurasia, with all of its closest relatives being viruses of monocotyledonous plants. Here we report that we have identified a sister lineage of TuMV-like potyviruses (TuMV-OM) from European orchids. The isolates of TuMV-OM form a monophyletic sister lineage to the brassica-infecting TuMVs (TuMV-BIs), and are nested within a clade of monocotyledon-infecting viruses. Extensive host-range tests showed that all of the TuMV-OMs are biologically similar to, but distinct from, TuMV-BIs and do not readily infect brassicas. We conclude that it is more likely that TuMV evolved from a TuMV-OM-like ancestor than the reverse. We did Bayesian coalescent analyses using a combination of novel and published sequence data from four TuMV genes [helper component-proteinase protein (HC-Pro), protein 3(P3), nuclear inclusion b protein (NIb), and coat protein (CP)]. Three genes (HC-Pro, P3, and NIb), but not the CP gene, gave results indicating that the TuMV-BI viruses diverged from TuMV-OMs around 1000 years ago. Only 150 years later, the four lineages of the present global population of TuMV-BIs diverged from one another. These dates are congruent with historical records of the spread of agriculture in Western Europe. From about 1200 years ago, there was a warming of the climate, and agriculture and the human population of the region greatly increased. Farming replaced woodlands, fostering viruses and aphid vectors that could invade the crops, which included several brassica cultivars and weeds. Later, starting 500 years ago, inter-continental maritime trade probably spread the TuMV-BIs to the remainder of the world

Cold urticaria – What we know and what we do not know

Cold urticaria (ColdU) is a common form of chronic inducible urticaria characterized by the development of wheals, angioedema or both in response to cold exposure. Recent research and guideline updates have advanced our understanding and management of ColdU. Today, its pathophysiology is thought to involve the cold-induced formation of autoallergens and IgE to these autoallergens, which provoke a release of proinflammatory mediators from skin mast cells. The classification of ColdU includes typical and atypical subtypes. We know that cold-induced wheals usually develop on rewarming and resolve within an hour and that anaphylaxis can occur. The diagnosis relies on the patient's history and cold stimulation testing. Additional diagnostic work-up, including a search for underlying infections, should only be done if indicated by the patient's history. The management of ColdU includes cold avoidance, the regular use of nonsedating antihistamines and the off-label use of omalizumab. However, many questions regarding ColdU remain unanswered. Here, we review what is known about ColdU, and we present important unanswered questions on the epidemiology, underlying pathomechanisms, clinical heterogeneity and treatment outcomes. Our aim is to guide future efforts that will close these knowledge gaps and advance the management of ColdU

Statistical challenges in assessing potential efficacy of complex interventions in pilot or feasibility studies

Early phase trials of complex interventions currently focus on assessing the feasibility of a large RCT and on conducting pilot work. Assessing the efficacy of the proposed intervention is generally discouraged, due to concerns of underpowered hypothesis testing. In contrast, early assessment of efficacy is common for drug therapies, where phase II trials are often used as a screening mechanism to identify promising treatments. In this paper we outline the challenges encountered in extending ideas developed in the phase II drug trial literature to the complex intervention setting. The prevalence of multiple endpoints and clustering of outcome data are identified as important considerations, having implications for timely and robust determination of optimal trial design parameters. The potential for Bayesian methods to help to identify robust trial designs and optimal decision rules is also explored

Mitigation-driven translocations: are we moving wildlife in the right direction?

Despite rapid growth in the field of reintroduction biology, many lessons learned from scientific research are not being applied to translocations initiated when human land-use conflicts with persistence of a species. Mitigation-driven translocations outnumber and receive better funding than science-based conservation translocations worldwide, yet their conservation benefit is unclear. As mitigation releases are economically motivated, outcomes may diverge greatly from releases designed to serve the biological needs of species. Translocation as a regulatory tool may be ill-fitted to biologically mitigate environmental damage wrought by development. Evidence suggests that many mitigation-driven translocations fail, though application of scientific principles and best-practices could likely increase success. Furthermore, lack of transparency and documentation of outcomes hinder efforts to understand the scope of the problem. If mitigation-driven translocations continue unabated as a part of the growing billion-dollar ecological consulting industry, it is imperative that the scale and effects of these releases are reported and evaluated

Effects of UV-B radiation on the structural and physiological diversity of bacterioneuston and bacterioplankton

The effects of UV radiation (UVR) on estuarine bacterioneuston and bacterioplankton were assessed in microcosm experiments. Bacterial abundance and DNA synthesis were more affected in bacterioplankton. Protein synthesis was more inhibited in bacterioneuston. Community analysis indicated that UVR has the potential to select resistant bacteria (e.g., Gammaproteobacteria), particularly abundant in bacterioneuston

Dramatic age-related changes in nuclear and genome copy number in the nematode Caenorhabditis elegans

The nematode Caenorhabditis elegans has become one of the most widely used model systems for the study of aging, yet very little is known about how C. elegans age. The development of the worm, from egg to young adult has been completely mapped at the cellular level, but such detailed studies have not been extended throughout the adult lifespan. Numerous single gene mutations, drug treatments and environmental manipulations have been found to extend worm lifespan. To interpret the mechanism of action of such aging interventions, studies to characterize normal worm aging, similar to those used to study worm development are necessary. We have used 4′,6′-diamidino-2-phenylindole hydrochloride staining and quantitative polymerase chain reaction to investigate the integrity of nuclei and quantify the nuclear genome copy number of C. elegans with age. We report both systematic loss of nuclei or nuclear DNA, as well as dramatic age-related changes in nuclear genome copy number. These changes are delayed or attenuated in long-lived daf-2 mutants. We propose that these changes are important pathobiological characteristics of aging nematodes