Topology and energy transport in networks of interacting photosynthetic complexes

We address the role of topology in the energy transport process that occurs in networks of photosynthetic complexes. We take inspiration from light harvesting networks present in purple bacteria and simulate an incoherent dissipative energy transport process on more general and abstract networks, considering both regular structures (Cayley trees and hyperbranched fractals) and randomly-generated ones. We focus on the the two primary light harvesting complexes of purple bacteria, i.e., the LH1 and LH2, and we use network-theoretical centrality measures in order to select different LH1 arrangements. We show that different choices cause significant differences in the transport efficiencies, and that for regular networks centrality measures allow to identify arrangements that ensure transport efficiencies which are better than those obtained with a random disposition of the complexes. The optimal arrangements strongly depend on the dissipative nature of the dynamics and on the topological properties of the networks considered, and depending on the latter they are achieved by using global vs. local centrality measures. For randomly-generated networks a random arrangement of the complexes already provides efficient transport, and this suggests the process is strong with respect to limited amount of control in the structure design and to the disorder inherent in the construction of randomly-assembled structures. Finally, we compare the networks considered with the real biological networks and find that the latter have in general better performances, due to their higher connectivity, but the former with optimal arrangements can mimic the real networks' behaviour for a specific range of transport parameters. These results show that the use of network-theoretical concepts can be crucial for the characterization and design of efficient artificial energy transport networks.Comment: 14 pages, 16 figures, revised versio

Technical note: Problem-specific variators in a genetic algorithm for the optimization of drinking water networks

Genetic algorithms can be a powerful tool for the automated design of optimal drinking water distribution networks. Fast convergence of such algorithms is a crucial factor for successful practical implementation at the drinking water utility level. In this technical note, we therefore investigate the performance of a suite of genetic variators that was tailored to the optimization of a least-cost network design. Different combinations of the variators are tested in terms of convergence rate and the robustness of the results during optimization of the real-world drinking water distribution network of Sittard, the Netherlands. The variator configurations that reproducibly reach the furthest convergence after 105 function evaluations are reported. In the future these may aid in dealing with the computational challenges of optimizing real-world networks.</p

Applicative Bidirectional Programming with Lenses

A bidirectional transformation is a pair of mappings between source and view data objects, one in each direction. When the view is modified, the source is updated accordingly with respect to some laws. One way to reduce the development and maintenance effort of bidirectional transformations is to have specialized languages in which the resulting programs are bidirectional by construction---giving rise to the paradigm of bidirectional programming. In this paper, we develop a framework for applicative-style and higher-order bidirectional programming, in which we can write bidirectional transformations as unidirectional programs in standard functional languages, opening up access to the bundle of language features previously only available to conventional unidirectional languages. Our framework essentially bridges two very different approaches of bidirectional programming, namely the lens framework and Voigtlander’s semantic bidirectionalization, creating a new programming style that is able to bag benefits from both

Risk Prediction in Acute Calculous Cholecystitis: A Systematic Review and Meta-analysis of Prognostic Factors and Predictive Models

BACKGROUND: Laparoscopic cholecystectomy is the main treatment of acute cholecystitis. Although considered relatively safe, it carries 6%–9% risk of major complications and 0.1%–1% risk of mortality. There is no consensus regarding the evaluation of the preoperative risks, and the management of patients with acute cholecystitis is usually guided by surgeon's personal preferences. We assessed the best method to identify patients with acute cholecystitis who are at high risk of complications and mortality. METHODS: We performed a systematic review of studies that reported the preoperative prediction of outcomes in people with acute cholecystitis. We searched the Cochrane Library, MEDLINE, EMBASE, WHO ICTRP, ClinicalTrials.gov, and Science Citation Index Expanded until April 27, 2019. We performed a meta-analysis when possible. RESULTS: Six thousand eight hundred twenty-seven people were included in one or more analyses in 12 studies. Tokyo guidelines 2013 (TG13) predicted mortality (two studies; Grade 3 versus Grade 1: odds ratio [OR] 5.08, 95% confidence interval [CI] 2.79–9.26). Gender predicted conversion to open cholecystectomy (two studies; OR 1.59, 95% CI 1.06–2.39). None of the factors reported in at least two studies had significant predictive ability of major or minor complications. CONCLUSION: There is significant uncertainty in the ability of prognostic factors and risk prediction models in predicting outcomes in people with acute calculous cholecystitis. Based on studies of high risk of bias, TG13 Grade 3 severity may be associated with greater mortality than Grade 1. Early referral of such patients to high-volume specialist centers should be considered. Further well-designed prospective studies are necessary

In-One-Continuity Rectal Excision and Anal Mucosectomy of a Giant Villous Adenoma: An Alternative Surgical Approach

Background: The authors present a woman suffering from McKittrick-Wheelock syndrome (MKWS) with a giant rectal villous adenoma. MKWS is a rare disorder caused by fluid and electrolyte hypersecretion from a rectal tumor. The most frequently reported tumors are villous adenomas. Symptoms of dehydration with severe hyponatremia, hypokalemia, metabolic acidosis and acute renal failure are typical in MKWS. Several options for operation have been reported, such as a transsacral approach (according to Kraske), transanal endoscopic microsurgery (TEM) or total mesorectal excision (TME). In this case we report an alternative surgical approach: in-one-continuity transanal mucosectomy and transabdominal TME with a handsewn colonic-anal anastomosis. Case: A 54-year-old woman had a history of hospital admissions because of repeated bouts of dehydration with electrolyte disorders since 2004. At admission she presented with prerenal azotemia, hyponatremia and severe hypokalemia in combination with watery stools. At colonoscopy an 8-cm villous adenoma was seen in the rectum. Dehydration and electrolyte disturbances were treated by appropriate intravenous fluid administration. An in-one-continuity anal mucosectomy and complete rectal excision were performed and restored by a handmade colonic-anal anastomosis. Postoperative recovery was uneventful. Conclusion: MKWS can be a difficult problem to assess in both gastroenterological and nephrological ways. Patients may develop severe complications which require surgical intervention in some cases. In-one-continuity transanal mucosectomy and rectum excision with a handmade colonic-anal anastomosis seemed to be a new and solid surgical therapeutic option in this case

Simultaneous ultrafast probing of intramolecular vibrations and photoinduced charge carriers in rubrene using broadband time-domain THz spectroscopy

The ultrafast frequency- and time-resolved complex dielec. responses of photoexcited, single-crystal rubrene at n = 10-30 THz were detd. using ultrafast broadband far-IR spectra. In this frequency range, the responses of both photogenerated mobile charges and intramol. vibrational modes were obsd. simultaneously, both of which vary with time after excitation. The data in conjunction with a theor. model indicate a dynamic blueshift of the 15.5 THz phonon. [on SciFinder (R)

Monte Carlo Methods for Rough Free Energy Landscapes: Population Annealing and Parallel Tempering

Parallel tempering and population annealing are both effective methods for simulating equilibrium systems with rough free energy landscapes. Parallel tempering, also known as replica exchange Monte Carlo, is a Markov chain Monte Carlo method while population annealing is a sequential Monte Carlo method. Both methods overcome the exponential slowing associated with high free energy barriers. The convergence properties and efficiency of the two methods are compared. For large systems, population annealing initially converges to equilibrium more rapidly than parallel tempering for the same amount of computational work. However, parallel tempering converges exponentially and population annealing inversely in the computational work so that ultimately parallel tempering approaches equilibrium more rapidly than population annealing.Comment: 10 pages, 3 figure

Fecal Microbiota Transplantation from Overweight or Obese Donors in Cachectic Patients with Advanced Gastroesophageal Cancer : A Randomized, Double-blind, Placebo-Controlled, Phase II Study

Purpose Cachexia is a multifactorial syndrome, associated with poor survival in patients with cancer, and is influenced by the gut microbiota. We investigated the effects of fecal microbiota transplantation (FMT) on cachexia and treatment response in patients with advanced gastroesophageal cancer. Experimental Design: In a double-blind randomized placebo-controlled trial performed in the Amsterdam University Medical Center, we assigned 24 cachectic patients with metastatic HER2-negative gastroesophageal cancer to either allogenic FMT (healthy obese donor) or autologous FMT, prior to palliative chemotherapy (capecitabine and oxaliplatin). Primary objective was to assess the effect of allogenic FMT on satiety. Secondary outcomes were other features of cachexia, along with disease control rate (DCR), overall survival (OS), progression-free survival (PFS), and toxicity. Finally, exploratory analyses were performed on the effect of FMT on gut microbiota composition (metagenomic sequencing) and metabolites (untargeted metabolomics). Results: Allogenic FMT did not improve any of the cachexia outcomes. Patients in the allogenic group (n = 12) had a higher DCR at 12 weeks (P = 0.035) compared with the autologous group (n = 12), longer median OS of 365 versus 227 days [ HR = 0.38; 95% confidence interval (CI), 0.14-1.05; P = 0.057] and PFS of 204 versus 93 days (HR = 0.50; 95% CI, 0.21-1.20; P = 0.092). Patients in the allogenic group showed a significant shift in fecal microbiota composition after FMT (P = 0.010) indicating proper engraftment of the donor microbiota. Conclusions: FMT from a healthy obese donor prior to first-line chemotherapy did not affect cachexia, but may have improved response and survival in patients with metastatic gastroesophageal cancer. These results provide a rational for larger FMT trials.Peer reviewe

Cyber Security: China and Russia\u27s Erosion of 21st Century United States\u27 Hegemony

With Russia and China emerging as challengers to U.S. hegemony, the use of cyber warfare could tilt the current balance of power in either of their favors. Using various methods, hackers can acquire sensitive information and destroy online infrastructures. In the development of cyber warfare, China has become a seasoned veteran with computer virus operations dating back to 199714. Russia has emerged as a cyber aggressor, as seen in Russia’s cyber attacks on several countries in the last decade. This paper argues that, with the growth of foreign cyber technology, the probability of cyberspace being used as a military front by state or non-state actors against the United States increases

GEMSEC: Graph Embedding with Self Clustering

Modern graph embedding procedures can efficiently process graphs with millions of nodes. In this paper, we propose GEMSEC -- a graph embedding algorithm which learns a clustering of the nodes simultaneously with computing their embedding. GEMSEC is a general extension of earlier work in the domain of sequence-based graph embedding. GEMSEC places nodes in an abstract feature space where the vertex features minimize the negative log-likelihood of preserving sampled vertex neighborhoods, and it incorporates known social network properties through a machine learning regularization. We present two new social network datasets and show that by simultaneously considering the embedding and clustering problems with respect to social properties, GEMSEC extracts high-quality clusters competitive with or superior to other community detection algorithms. In experiments, the method is found to be computationally efficient and robust to the choice of hyperparameters