Machine Learning is the study of methods for programming computers to learn. Computers are applied to a wide range of tasks, and for most of these it is relatively easy for programmers to design and implement the necessary software. However, there are many tasks for which this is difficult or impossible. These can be divided into four general categories. First, there are problems for which there exist no human experts. For example, in modern automated manufacturing facilities, there is a need to predict machine failures before they occur by analyzing sensor readings. Because the machines are new, there are no human experts who can be interviewed by a programmer to provide the knowledge necessary to build a computer system. A machine learning system can study recorded data and subsequent machine failures and learn prediction rules. Second, there are problems where human experts exist, but where they are unable to explain their expertise. This is the case in many perceptual tasks, such as speech recognition, hand-writing recognition, and natural language understanding. Virtually all humans exhibit expert-level abilities on these tasks, but none of them can describe the detailed steps that they follow as they perform them. Fortunately, humans can provide machines with examples of the inputs and correct outputs for these tasks, so machine learning algorithms can learn to map the inputs to the outputs. Third, there are problems where phenomena are changing rapidly. In finance, for example, people would like to predict the future behavior of the stock market, of consumer purchases, or of exchange rates. These behaviors change frequently, so that even if a programmer could construct a good predictive computer program, it would need to be rewritten frequently. A learning program can relieve the programmer of this burden by constantly modifying and tuning a set of learned prediction rules. Fourth, there are applications that need to be customized for each computer user separately. Consider, for example, a program to filter unwanted electronic mail messages. Different users will need different filters. It is unreasonable to expect each user to program his or her own rules, and it is infeasible to provide every user with a software engineer to keep the rules up-to-date. A machine learning system can learn which mail messages the user rejects and maintain the filtering rules automatically. Machine learning addresses many of the same research questions as the fields of statistics, data mining, and psychology, but with differences of emphasis. Statistics focuses on understanding the phenomena that have generated the data, often with the goal of testing different hypotheses about those phenomena. Data mining seeks to find patterns in the data that are understandable by people. Psychological studies of human learning aspire to understand the mechanisms underlying the various learning behaviors exhibited by people (concept learning, skill acquisition, strategy change, etc.).

Machine learning

The world is in the grip of the COVID-19 pandemic. Public health measures that can reduce the risk of infection and death in addition to quarantines are desperately needed. This article reviews the roles of vitamin D in reducing the risk of respiratory tract infections, knowledge about the epidemiology of influenza and COVID-19, and how vitamin D supplementation might be a useful measure to reduce risk. Through several mechanisms, vitamin D can reduce risk of infections. Those mechanisms include inducing cathelicidins and defensins that can lower viral replication rates and reducing concentrations of pro-inflammatory cytokines that produce the inflammation that injures the lining of the lungs, leading to pneumonia, as well as increasing concentrations of anti-inflammatory cytokines. Several observational studies and clinical trials reported that vitamin D supplementation reduced the risk of influenza, whereas others did not. Evidence supporting the role of vitamin D in reducing risk of COVID-19 includes that the outbreak occurred in winter, a time when 25-hydroxyvitamin D (25(OH)D) concentrations are lowest; that the number of cases in the Southern Hemisphere near the end of summer are low; that vitamin D deficiency has been found to contribute to acute respiratory distress syndrome; and that case-fatality rates increase with age and with chronic disease comorbidity, both of which are associated with lower 25(OH)D concentration. To reduce the risk of infection, it is recommended that people at risk of influenza and/or COVID-19 consider taking 10,000 IU/d of vitamin D3 for a few weeks to rapidly raise 25(OH)D concentrations, followed by 5000 IU/d. The goal should be to raise 25(OH)D concentrations above 40–60 ng/mL (100–150 nmol/L). For treatment of people who become infected with COVID-19, higher vitamin D3 doses might be useful. Randomized controlled trials and large population studies should be conducted to evaluate these recommendations.

Evidence that Vitamin D Supplementation Could Reduce Risk of Influenza and COVID-19 Infections and Deaths.

Our Galaxy, the Milky Way, is a benchmark for understanding disk galaxies. It is the only galaxy whose formation history can be studied using the full distribution of stars from faint dwarfs to supergiants. The oldest components provide us with unique insight into how galaxies form and evolve over billions of years. The Galaxy is a luminous (L⋆) barred spiral with a central box/peanut bulge, a dominant disk, and a diffuse stellar halo. Based on global properties, it falls in the sparsely populated “green valley” region of the galaxy color-magnitude diagram. Here we review the key integrated, structural and kinematic parameters of the Galaxy, and point to uncertainties as well as directions for future progress. Galactic studies will continue to play a fundamental role far into the future because there are measurements that can only be made in the near field and much of contemporary astrophysics depends on such observations.

The Galaxy in Context: Structural, Kinematic, and Integrated Properties

Aims. The aim of this paper is to explore and map the age and abundance structure of the stars in the nearby Galactic disk. Methods. We have conducted a high-resolution spectroscopic study of 714 F and G dwarf and subgiant stars in the Solar neighbourhood. The star sample has been kinematically selected to trace the Galactic thin and thick disks to their extremes, the metal-rich stellar halo, sub-structures in velocity space such as the Hercules stream and the Arcturus moving group, as well as stars that cannot (kinematically) be associated with either the thin disk or the thick disk. The determination of stellar parameters and elemental abundances is based on a standard analysis using equivalent widths and one-dimensional, plane-parallel model atmospheres calculated under the assumption of local thermodynamical equilibrium (LTE). The spectra have high resolution (R = 40 000-110 000) and high signal-to-noise)S/V = 150-300) and were obtained with the FEROS spectrograph on the ESO 1.5 in and 2.2 in telescopes, the SOFIN and PIES spectrographs on the Nordic Optical Telescope, the LIVES spectrograph on the E50 Very Large Telescope, the HARPS spectrograph on the ESO 3.6 m telescope, and the MIKE spectrograph on the Magellan Clay telescope. The abundances from individual Fe I lines were were corrected for non-LTE effects in every step of the analysis. Results. We present stellar parameters, stellar ages, kinematical parameters, orbital parameters, and detailed elemental abundances for 0, Na, Mg, Al, Si, Ca, Ti, Cr, Fe, Ni, Zn, Y. and Ba for 714 nearby 12 and G dwarf stars. Our data show that there is an old and a-enhanced disk population, and a younger and less a-enhanced disk population. While they overlap greatly in metallicity between 0.7 < [Fe/HI] less than or similar to +0.1, they show a bimodal distribution in [alpha/Fe]. This bimodality becomes even clearer if stars where stellar parameters and abundances show larger uncertainties (T-eff less than or similar to 5400 K) are discarded, showing that it is important to constrain the data set to a narrow range in the stellar parameters if small differences between stellar populations are to be revealed. In addition, we find that the a-enhanced population has orbital parameters placing the stellar birthplaces in the inner Galactic disk while the loss-alpha stars mainly come from the outer Galactic disk, fully consistent with the recent claims of a short scale-length for the alpha-enhanced Galactic thick disk. We have also investigated the properties of the Hercules stream and the Arcturus moving group and find that neither of them presents chemical or age signatures that could suggest that they are disrupted clusters or extragalactic accretion remnants from ancient merger events. Instead, they are most likely dynamical features originating within the Galaxy. We have also discovered that a standard 1D. LTE analysis, utilising ionisation and excitation balance of Fe I and Fen lines produces a flat lower main sequence. As the exact cause for this effect is unclear we chose to apply an empirical correction. Turn-off stars and more evolved stars appear to be unaffected. (Less)

/pdf/exploring-the-milky-way-stellar-disk-a-detailed-elemental-2cyhvnbv0r.pdf

Exploring the Milky Way stellar disk - A detailed elemental abundance study of 714 F and G dwarf stars in the solar neighbourhood

This work aims to present our current best physical understanding of common-envelope evolution (CEE). We highlight areas of consensus and disagreement, and stress ideas which should point the way forward for progress in this important but long-standing and largely unconquered problem. Unusually for CEE-related work, we mostly try to avoid relying on results from population synthesis or observations, in order to avoid potentially being misled by previous misunderstandings. As far as possible we debate all the relevant issues starting from physics alone, all the way from the evolution of the binary system immediately before CEE begins to the processes which might occur just after the ejection of the envelope. In particular, we include extensive discussion about the energy sources and sinks operating in CEE, and hence examine the foundations of the standard energy formalism. Special attention is also given to comparing the results of hydrodynamic simulations from different groups and to discussing the potential effect of initial conditions on the differences in the outcomes. We compare current numerical techniques for the problem of CEE and also whether more appropriate tools could and should be produced (including new formulations of computational hydrodynamics, and attempts to include 3D processes within 1D codes). Finally we explore new ways to link CEE with observations. We compare previous simulations of CEE to the recent outburst from V1309 Sco, and discuss to what extent post-common-envelope binaries and nebulae can provide information, e.g. from binary eccentricities, which is not currently being fully exploited.

/pdf/common-envelope-evolution-where-we-stand-and-how-we-can-move-1aki8lp6t7.pdf

Common envelope evolution: where we stand and how we can move forward

On June 24, 2021 we published a risk-benefit analysis of COVID-19 vaccines, admittedly based on a shaky database. This analysis resulted in the insight, that very likely for three deaths prevented by vaccination we will have to accept that about two people die as a consequence of these vaccinations.1 This analysis led to editors’ threatening to withdraw, and the journal indeed retracted the publication. After a thorough re-review, it was republished.2, 3 The database we based our analysis on was a large naturalistic study of the BioNTech vaccine in Israel.4 This was the only study at the time that allowed for a direct estimation of an absolute risk reduction (ARR) in mortality. Admittedly, the ARR estimate was only available for a short observation period of 4 weeks after the first vaccine dose, a point raised by critics. One might have wanted a longer observation period to bring out the benefit of vaccinations more clearly, and our estimate of a number needed to vaccinate (NNV) of 16 000 to prevent one death might have been overly conservative. The recently published 6-month interim report of the BioNTech-regulatory clinical trial now covers a period long enough to let us look at this risk benefit ratio once again.5 In Table S4 of this publication,5 14 deaths are reported in the placebo group (n = 21 921) and 15 in the vaccination group (n = 21 926). Among them, two deaths in the placebo-group were attributed to COVID-19, and one in the vaccination group was attributed to COVID-19 pneumonia. This leads to an ARR = 4.56 × 10–5, and conversely to an NNV = 1/ARR = 21 916 to prevent one death by COVID-19. This shows that our original estimate was not so far off the mark. These passive pharmacovigilance data, different from the active reporting system of trials and observations, are notorious for underestimating casualties and side effects.6 Other severe side effects occur, such as myocarditis in young males who according to a recent study suffer a 13.6 fold risk of myocarditis.7 Thus, we have novel and worrying data that confirm the analysis we published in summer 2021, urging us to repeat our call for an installment of a European-wide active monitoring system that documents the safety and efficacy of COVID-19 vaccines long-term and for a rational public debate about the risk-benefit ratio of these novel vaccines. The authors declare that there is no conflict of interest that could be perceived as prejudicing the impartiality of the research reported. 

https://onlinelibrary.wiley.com/doi/pdfdirect/10.1002/ctd2.35

The risk‐benefit ratio of Covid‐19 vaccines: Publication policy by retraction does nothing to improve it

We here describe two apparent paradoxes concerning high CRP levels and NCD risk. One has emerged from observational studies in the Amazon region showing that the indigenous Tsimane in Bolivia appear protected against non-communicable diseases (NCDs) such as obesity, type 2 diabetes, and cardiovascular diseases despite increased inflammatory markers. These findings stand in contrast to Western societies, where an increasing body of evidence demonstrates that low-grade-inflammation is the driver of NCDs. The second paradox has emerged from two field studies (Eifel studies) conducted in 2013 and 2014 with Westerners who returned to a simulated Palaeolithic lifestyle in a National park for 4 days. We had detected elevated inflammation markers, despite otherwise anti-inflammatory effects of these interventions as indicated by metabolic blood parameters. We here propose three hypotheses for this second inflammatory paradox.

/pdf/the-inflammation-paradox-why-are-tsimane-protected-against-b8u741kwlv.pdf

The inflammation paradox: Why are Tsimane protected against Western diseases while Westerners are not?

There is a growing interest in a particular metabolic state and its influence on cancer therapy: ketosis. Ketosis denotes the physiological rise in ketone bodies that is proportional to fat oxidati...

https://www.tandfonline.com/doi/pdf/10.1080/14737140.2020.1747438

Addressing the controversial role of ketogenic diets in cancer treatment.

An efficient separation between dwarfs and giants in surveys of bright stars is important, especially for studies in which distances are estimated through photometric parallax relations. We use the available spectroscopic log g estimates from the second RAVE data release (DR2) to assign each star a probability for being a dwarf or subgiant/giant based on mixture model fits to the log g distribution in different color bins. We further attempt to use these stars as a labeled training set in order to classify stars which lack log g estimates into dwarfs and giants with a SVM algorithm. We assess the performance of this classification against different choices of the input feature vector. In particular, we use different combinations of reduced proper motions, 2MASS JHK, DENIS IJK and USNO-B B2R2 apparent magnitudes. Our study shows that -- for our color ranges -- the infrared bands alone provide no relevant information to separate dwarfs and giants. Even when optical bands and reduced proper motions are added, the fraction of true giants classified as dwarfs (the contamination) remains above 20%. 
Using only the dwarfs with available spectroscopic log g and distance estimates (the latter from Breddels et al. 2010), we then repeat the stream search by Klement, Fuchs & Rix (2008, KFR08), which assumed all stars were dwarfs and claimed the discovery of a new stellar stream at V = -160 km/s in a sample of 7015 stars from RAVE DR1. Our re-analysis of the pure DR2 dwarf sample exhibits an overdensity of 5 stars at the phase-space position of the KFR08 stream, with a metallicity distribution that appears inconsistent with that of stars at comparably low rotational velocities. Compared to several smooth Milky Way models, the mean standardized deviation of the KFR08 stream is only marginal at 1.6$\pm$0.4... (abbreviated)

Classification of field dwarfs and giants in RAVE and its use in stellar stream detection

Abdel-Rahman [1] analyzed the overall survival-rate and disease-free survival of T1-2 N1 breast cancer patients after mastectomy, who were adjuvantly treated with various modern chemotherapeutic drugs (anthracyclines, taxanes) in 3 prospective phase III chemotherapy trials. His analysis suggested no potential benefits of an additional adjuvant postmastectomy radiotherapy (PMRT). The included trials were the BIG 02/98 [6], the BCIRG 001 [7] and the BCIRG005 [5] trials. The author concludes that in T1-2 N1 breast cancer patients who have received modern chemotherapy drugs PMRT does not provide any benefit for overall and disease-free survival. Prospective studies are necessary.

Comment to Impact of postmastectomy radiotherapy on the outcomes of breast cancer patients with T1-2 N1 disease; an individual patient data analysis of three clinical trials.

Rainer J. Klement

Papers

The risk‐benefit ratio of Covid‐19 vaccines: Publication policy by retraction does nothing to improve it

The inflammation paradox: Why are Tsimane protected against Western diseases while Westerners are not?

Addressing the controversial role of ketogenic diets in cancer treatment.

Classification of field dwarfs and giants in RAVE and its use in stellar stream detection

Comment to Impact of postmastectomy radiotherapy on the outcomes of breast cancer patients with T1-2 N1 disease; an individual patient data analysis of three clinical trials.