Miracle-dz/UniFAR-FTUs huggingface dataset:
Crowdsourcing big data research on human history and health : from genealogies to genomes and back again

About two months ago, Science Magazine invited me to write a Perspective to appear in the same issue as “Quantitative analysis of population-scale family trees with millions of relatives” (AKA the Geni genealogy) by Joanna Kaplanis, Assaf Gordon et al. with Yaniv Erlich and many others. Realizing that this paper will be covered by everyone and their mother, I spent days aiming to come up with unique facts and perspectives, finding myself ensconced in what became research projects, reading dozens of articles, and going down multiple rabbit holes of writing. Nothing that I could have afforded doing within the 30 days I was given to produce the Perspective. Based on other papers I previously discussed with Science editors, though Kaplanis et al. assembled and analyzed genealogies, my mandate from Science was to cover crowdsourced studies in related fields as well, especially in genetics, and the state of these fields in general—past, present, and future. And the icing on the cake: All that in 1250 words (including references! ) Published today in Science (10.1126/science.aat2634), alongside the publication of Kaplanis et al. (of which a First Release appeared online in the interim), is our Perspective, not before removing many parts, frantically cutting down, and editing in several rounds, including with the gracious help of Science Perspective editor, of what has been a much, much longer draft. I thought to complement its publication with the following longerread version. While not as concise, I find it to be less cryptic to read, more accessible to a general audience, and comprehensive in discussing aspects of that important study and the state of the pertaining fields. If nothing else, I found it worthwhile for being able to use my full-length title (The Hobbit anybody? )
Decentralized Combinatorial Auctions for Multi-Unit Resource Allocation

Auction has been used to allocate resources or tasks to processes, machines or other autonomous entities in distributed systems. When different bidders have different demands and valuations on different types of resources or tasks, the auction becomes a combinatorial auction (CA), for which finding an optimal auction result that maximizes total winning bid is NP-hard. Many time-efficient approximations to this problem work with a bid ranking function (BRF). However, existing approximations are all centralized and mostly for single-unit resource. In this paper, we propose the first decentralized CA schemes for multi-unit resources. It includes a BRF-based winner determination scheme that enables every agent to locally compute a critical bid value for her to win the CA and accordingly take her best response to other agent's win declaration. It also includes a critical-value-based pricing scheme for each winner to locally compute her payment. We analyze stabilization, correctness, and consistency properties of the proposed approach. Simulation results confirms that the proposed approach identifies exactly the same set of winners as the centralized counterpart regardless of initial bid setting, but at the cost of lower total winning bid and payment.
Model-updated image-guided liver surgery: preliminary results using intra-operative surface characterization

The current protocol for image-guidance in liver surgeries involves rigid registration algorithm. Systematic studies have shown that the liver can deform up to 2cms during surgeries thereby compromising the accuracy of the surgical navigation systems. Compensating for intraoperative deformations using computational models has shown promising results. In this work, we follow up the initial rigid registration with a computational approach. The proposed computational approach relies on the closest point distances between the undeformed pre-operative surface and the rigidly registered deformed intra-operative surface. We also introduce a spatial smoothing filter to generate a realistic deformation field using the closest point distances. The proposed approach was validated in both phantom experiments and clinical cases. Preliminary results are encouraging and suggest that computational models can be used to improve the accuracy of image-guided liver surgeries.
Impact of a Prospective Audit and Feedback Antimicrobial Stewardship Program at a Veterans Affairs Medical Center: A Six-Point Assessment

Background Prospective audit and feedback is a core antimicrobial stewardship program (ASP) strategy; however its impact is difficult to measure. Methods Our quasi-experimental study measured the effect of an ASP on clinical outcomes, antimicrobial use, resistance, costs, patient safety (adverse drug events [ADE] and Clostridium difficile infection [CDI]), and process metrics pre- (9/10–10/11) and post-ASP (9/12–10/13) using propensity adjusted and matched Cox proportional-hazards regression models and interrupted time series (ITS) methods. Results Among our 2,696 patients, median length of stay was 1 day shorter post-ASP (5, interquartile range [IQR] 3–8 vs. 4, IQR 2–7 days, p<0.001). Mortality was similar in both periods. Mean broad-spectrum (-11.3%), fluoroquinolone (-27.0%), and anti-pseudomonal (-15.6%) use decreased significantly (p<0.05). ITS analyses demonstrated a significant increase in monthly carbapenem use post-ASP (trend: +1.5 days of therapy/1,000 patient days [1000PD] per month; 95% CI 0.1–3.0). Total antimicrobial costs decreased 14%. Resistance rates did not change in the one-year post-ASP period. Mean CDI rates/10,000PD were low pre- and post-ASP (14.2 ± 10.4 vs. 13.8 ± 10.0, p = 0.94). Fewer patients experienced ADEs post-ASP (6.0% vs. 4.4%, p = 0.06). Conclusions Prospective audit and feedback has the potential to improve antimicrobial use and outcomes, and contain bacterial resistance. Our program demonstrated a trend towards decreased length of stay, broad-spectrum antimicrobial use, antimicrobial costs, and adverse events.
Mining Overlapping Communities and Inner Role Assignments through Bayesian Mixed-Membership Models of Networks with Context-Dependent Interactions

Community discovery and role assignment have been recently integrated into an unsupervised approach for the exploratory analysis of overlapping communities and inner roles in networks. However, the formation of ties in these prototypical research efforts is not truly realistic, since it does not account for a fundamental aspect of link establishment in real-world networks, i.e., the explicative reasons that cause interactions among nodes. Such reasons can be interpreted as generic requirements of nodes, that are met by other nodes and essentially pertain both to the nodes themselves and to their interaction contexts (i.e., the respective communities and roles). In this article, we present two new model-based machine-learning approaches, wherein community discovery and role assignment are seamlessly integrated and simultaneously performed through approximate posterior inference in Bayesian mixed-membership models of directed networks. The devised models account for the explicative reasons governing link establishment in terms of node-specific and contextual latent interaction factors. The former are inherently characteristic of nodes, while the latter are characterizations of nodes in the context of the individual communities and roles. The generative process of both models assigns nodes to communities with respective roles and connects them through directed links, which are probabilistically governed by their node-specific and contextual interaction factors. The difference between the proposed models lies in the exploitation of the contextual interaction factors. More precisely, in one model, the contextual interaction factors have the same impact on link generation. In the other model, the contextual interaction factors are weighted by the extent of involvement of the linked nodes in the respective communities and roles. We develop MCMC algorithms implementing approximate posterior inference and parameter estimation within our models. Finally, we conduct an intensive comparative experimentation, which demonstrates their superiority in community compactness and link prediction on various real-world and synthetic networks.
A Deterministic Distributed Algorithm for Exact Weighted All-Pairs Shortest Paths in Õ(n 3/2 ) Rounds

We present a deterministic distributed algorithm to compute all-pairs shortest paths (APSP) in an edge-weighted directed or undirected graph. Our algorithm runs in Õ (n^3/2 ) rounds in the Congest model, where n is the number of nodes in the graph. This is the first o(n^2) rounds deterministic distributed algorithm for the weighted APSP problem. Our algorithm is fairly simple and incorporates a deterministic distributed algorithm we develop for computing a 'blocker set' [King99], which has been used earlier in sequential dynamic computation of APSP.
Automatic Modulation Classification of Radar Signals Using the Pseudo Margenau-Hill Distribution

In a non-cooperative environment, it is difficult for an electronic intelligence (ELINT) receiver to implement intra-pulse modulation classification. This paper presents an approach based on the Pseudo Margenau-Hill distribution (PMHD). The algorithm computes the PMHD of the detected radar signals and extracts the ridges. Then, it defines three characteristic features, namely, the coefficient of piecewice linear fitting, the hop number of the ridge and the coefficient of inverted V Shape and realises the automatic modulation classification (AMC) of four kinds of radar signals under negative signal to noise ratio (SNR). The probability of successful recognition (PSR) is greater than 90%.
Spin and momentum of the light fields in inhomogeneous dispersive media with application to surface plasmon-polariton waves

Following to the recently published approach [Phys. Rev. Lett. 119, 073901 (2017); New J. Phys., 19, 123014 (2017)], we refine and accomplish the general scheme for the unified description of the momentum and angular momentum in complex media. The equations for the canonical (orbital) and spin linear momenta, orbital and spin angular momenta in a lossless inhomogeneous dispersive medium are presented in the compact form analogous to the Brillouin’s relation for the energy. The results are applied to the surface plasmon-polariton (SPP) field, and the microscopic calculations support the phenomenological expectations. The refined general scheme correctly describes the unusual SPP properties (transverse spin, magnetization momentum) and additionally predicts the singular momentum contribution sharply localized at the metal-dielectric interface, which is confirmed by the microscopic analysis. The results can be useful in optical systems employing the structured light, especially for microoptics, plasmophotonics, optical sorting and micromanipulation.
Interferon Independent Non-Canonical STAT Activation and Virus Induced Inflammation

Interferons (IFNs) are a group of secreted proteins that play critical roles in antiviral immunity, antitumor activity, activation of cytotoxic T cells, and modulation of host immune responses. IFNs are cytokines, and bind receptors on cell surfaces to trigger signal transduction. The major signaling pathway activated by IFNs is the JAK/STAT (Janus kinase/signal transducer and activator of transcription) pathway, a complex pathway involved in both viral and host survival strategies. On the one hand, viruses have evolved strategies to escape from antiviral host defenses evoked by IFN-activated JAK/STAT signaling. On the other hand, viruses have also evolved to exploit the JAK/STAT pathway to evoke activation of certain STATs that somehow promote viral pathogenesis. In this review, recent progress in our understanding of the virus-induced IFN-independent STAT signaling and its potential roles in viral induced inflammation and pathogenesis are summarized in detail, and perspectives are provided.
Power efficiency optimisation of wireless-powered full-duplex relay systems

In this study, the authors study the power efficiency optimisation in wireless-powered full-duplex relay (WFR) systems, where the entire transmission process can be partitioned into wireless power transfer phase (WP) and full-duplex information transmission phase (FP). For WFR systems with same source transmit power, where the source transmit powers of WP and FP are same, they first prove that the power efficiency is a strictly concave function over the time-switching factor, and an optimal time allocation scheme is proposed to maximise the power efficiency. Then, for the given time-switching protocol, the optimal power allocation strategy is obtained by analysing the derivative of the power efficiency with respect to the transmit power. Finally, they propose the joint power and time allocation scheme. For WFR systems with different source transmit power, where the source transmit powers of WP and FP are different, the optimal time allocation scheme and optimal power allocation strategy are derived by studying the derivative of the power efficiency. Furthermore, the joint power and time allocation scheme is proposed to maximise the power efficiency. Simulation results are presented to validate the authors' proposed schemes for the WFR systems.
DynCam: A Reactive Multithreaded Pipeline Library for 3D Telepresence in VR

We contribute a new library, DynCam, for real-time, low latency, streaming point cloud processing with a special focus on telepresence in VR. Our library combines several RGBD-images from multiple distributed sources to a single point cloud and transfers it through a network. This processing is organized as a pipeline that supports implicit multithreading. The pipeline uses functional reactive programming to describe transformations on the data in a declarative way. In contrast to previous libraries, DynCam is platform independent, modular and lightweight. This makes it easy to extend and allows easy integration into existing applications. We have prototypically implemented a telepresence application in the Unreal Engine. Our results show that DynCam outperforms competing libraries concerning latency as well as network traffic.
Economic Development Challenges for Immigrant Retail Corridors: Observations From Chicago’s Devon Avenue

Immigrant entrepreneurship is important to local and regional economies, cultural identity, placemaking, and tourism. Meanwhile, regional conditions, such as the development of suburban immigrant gateway communities and increases in the cost of business ownership, complicate local economic development efforts in urban ethnic districts. This research is presented as a mixed–methods case study of Devon Avenue in Chicago, IL, home to a significant concentration of South Asian–owned immigrant businesses. Challenges and pressures facing businesses are examined through merchant surveys and interviews. Observations reinforce the notion that cultural competency and strong grassroots leadership is vital for economic development planning so that “capitalizing” on an ethnic heritage does not become a tool for commodification or commercial gentrification. Agencies must also be mindful of the impacts associated with suburbanization of immigrant communities and take a long-term, regional approach to planning in ethnic commercial corridors.
Lawrence Berkeley National Laboratory Recent Work Title Exploring cosmic origins with CORE : gravitational lensing of the CMB Permalink

Lensing of the cosmic microwave background (CMB) is now a well-developed probe of the clustering of the large-scale mass distribution over a broad range of redshifts. By exploiting the non-Gaussian imprints of lensing in the polarization of the CMB, the CORE mission will allow production of a clean map of the lensing deflections over nearly the full-sky. The number of high-S/N modes in this map will exceed current CMB lensing maps by a factor of 40, and the measurement will be sample-variance limited on all scales where linear theory is valid. Here, we summarise this mission product and discuss the science that will follow from its power spectrum and the cross-correlation with other clustering data. For example, the summed mass of neutrinos will be determined to an accuracy of 17 meV combining CORE lensing and CMB two-point information with contemporaneous measurements of the baryon acoustic oscillation feature in the clustering of galaxies, three times smaller than the minimum total mass allowed by neutrino oscillation measurements. Lensing has applications across many other science goals of CORE, including the search for B-mode polarization from primordial gravitational waves. Here, lens-induced B-modes will dominate over instrument noise, limiting constraints on the power spectrum amplitude of primordial gravitational waves. With lensing reconstructed by CORE, one can “delens” the observed polarization internally, reducing the lensing B-mode power by 60 %. This can be improved to 70 % by combining lensing and measurements of the cosmic infrared background from CORE, leading to an improvement of a factor of 2.5 in the error on the amplitude of primordial gravitational waves compared to no delensing (in the null hypothesis of no primordial B-modes). Lensing measurements from CORE will allow calibration of the halo masses of the tens of thousands of galaxy clusters that it will find, with constraints dominated by the clean polarization-based estimators. The 19 frequency channels proposed for CORE will allow accurate removal of Galactic emission from CMB maps. We present initial findings that show that residual Galactic foreground contamination will not be a significant source of bias for lensing power spectrum measurements with CORE.
GLASSgo – Automated and Reliable Detection of sRNA Homologs From a Single Input Sequence

Bacterial small RNAs (sRNAs) are important post-transcriptional regulators of gene expression. The functional and evolutionary characterization of sRNAs requires the identification of homologs, which is frequently challenging due to their heterogeneity, short length and partly, little sequence conservation. We developed the GLobal Automatic Small RNA Search go (GLASSgo) algorithm to identify sRNA homologs in complex genomic databases starting from a single sequence. GLASSgo combines an iterative BLAST strategy with pairwise identity filtering and a graph-based clustering method that utilizes RNA secondary structure information. We tested the specificity, sensitivity and runtime of GLASSgo, BLAST and the combination RNAlien/cmsearch in a typical use case scenario on 40 bacterial sRNA families. The sensitivity of the tested methods was similar, while the specificity of GLASSgo and RNAlien/cmsearch was significantly higher than that of BLAST. GLASSgo was on average ∼87 times faster than RNAlien/cmsearch, and only ∼7.5 times slower than BLAST, which shows that GLASSgo optimizes the trade-off between speed and accuracy in the task of finding sRNA homologs. GLASSgo is fully automated, whereas BLAST often recovers only parts of homologs and RNAlien/cmsearch requires extensive additional bioinformatic work to get a comprehensive set of homologs. GLASSgo is available as an easy-to-use web server to find homologous sRNAs in large databases.
Acyl chain asymmetry and polyunsaturation of brain phospholipids facilitate membrane vesiculation without leakage

Phospholipid membranes form cellular barriers but need to be flexible enough to divide by fission. Phospholipids generally contain a saturated fatty acid (FA) at position sn1 whereas the sn2-FA is saturated, monounsaturated or polyunsaturated. Our understanding of the impact of phospholipid unsaturation on membrane flexibility and fission is fragmentary. Here, we provide a comprehensive view of the effects of the FA profile of phospholipids on membrane vesiculation by dynamin and endophilin. Coupled to simulations, this analysis indicates that: (i) phospholipids with two polyunsaturated FAs make membranes prone to vesiculation but highly permeable; (ii) asymmetric sn1-saturated-sn2-polyunsaturated phospholipids provide a tradeoff between efficient membrane vesiculation and low membrane permeability; (iii) When incorporated into phospholipids, docosahexaenoic acid (DHA; omega-3) makes membranes more deformable than arachidonic acid (omega-6). These results suggest an explanation for the abundance of sn1-saturated-sn2-DHA phospholipids in synaptic membranes and for the importance of the omega-6/omega-3 ratio on neuronal functions.
Cascades and Dissipative Anomalies in Nearly Collisionless Plasma Turbulence

We develop first-principles theory of kinetic plasma turbulence governed by the Vlasov-Maxwell-Landau equations in the limit of vanishing collision rates. Following an exact renormalization-group approach pioneered by Onsager, we demonstrate the existence of a "collisionless range" of scales (lengths and velocities) in 1-particle phase space where the ideal Vlasov-Maxwell equations are satisfied in a "coarse-grained sense". Entropy conservation may nevertheless be violated in that range by a "dissipative anomaly" due to nonlinear entropy cascade. We derive "4/5th-law" type expressions for the entropy flux, which allow us to characterize the singularities (structure-function scaling exponents) required for its non-vanishing. Conservation laws of mass, momentum and energy are not afflicted with anomalous transfers in the collisionless limit. In a subsequent limit of small gyroradii, however, anomalous contributions to inertial-range energy balance may appear due both to cascade of bulk energy and to turbulent redistribution of internal energy in phase space. In that same limit the "generalized Ohm's law" derived from the particle momentum balances reduces to an "ideal Ohm's law", but only in a coarse-grained sense that does not imply magnetic flux-freezing and that permits magnetic reconnection at all inertial-range scales. We compare our results with prior theory based on the gyrokinetic (high gyro-frequency) limit, with numerical simulations, and with spacecraft measurements of the solar wind and terrestrial magnetosphere.
Combined GSTM1 and GSTT1 null genotypes are strong risk factors for atherogenesis in a Serbian population

Abstract Oxidative stress (OS) plays an important role in atherogenesis and since glutathione S-transferases (GSTs) provide protection against OS, we have tested the hypothesis that deletion polymorphisms in two GSTs (GSTM1 and GSTT1) may affect the risk of developing atherosclerosis. A total of 382 individuals (200 patients with atherosclerosis and 182 healthy controls) were included in this association study. Genomic DNA was isolated from peripheral blood cells or from buccal epithelial cells and genotyping was performed using multiplex-PCR or real-time PCR methods. GSTM1 null genotype was significantly more frequent in atherosclerotic patients than in controls (52.0% vs 34.1%) and individuals with the GSTM1 null genotype had an approximately 2-fold increase in atherosclerosis risk (OR: 2.1, 95%CI=1.39-3.17, P=0.0004). GSTT1 null genotype alone did not show a statistically significant effect on atherosclerosis risk modulation, but the association approached significance (OR: 1.57, 95%CI=0.94-2.64, P=0.08). The combined analysis showed that the presence of both genes had a protective effect against atherosclerosis (OR=0.55, 95%CI=0.37-0.83, P=0.005) while double null genotypes led to a robust atherosclerosis risk increase (OR: 8.14, 95%CI= 2.41-27.51, P < 0.0001). This study demonstrated that the GSTM1 null and combined GSTM1/GSTT1 null genotypes are susceptibility factors for development of atherosclerosis in a Serbian population.