question:You will be shown an abstract from a biomedical research paper. Given this abstract, your task is to extract all unique entities of the following types: ["Brand", "UnapprovedDrug", "Drug", "DrugGroup"].Please return the output as a JSON object of the format: {"Brand" : ["Aspirin", ...], "DrugGroup": ["Salicyclate", ...], "Drug": ["Phenobarbital", ...], "UnapprovedDrug": ["Heroin", ...]}. The keys should be entity types and values should be lists of extracted entities belonging to the corresponding type. If you cannot find entities belonging to a specific type, the value should be [].Only output the JSON object and do not include any additional text.Abstract:Ketoconazole/Itraconazole, Macrolides, Including Erythromycin

question:You are provided with the abstract of a scientific paper and the abstracts of the papers it references. Your task is to write a Related Work section for the main paper. This section should concisely summarize and integrate the key points from the cited abstracts, reflecting how they relate to the main paper's contributions and context. In your summary, use numerical citation markers like [1], [2], etc., to refer to the corresponding papers.Main Abstract:For realistic scale-free networks, we investigate the traffic properties of stochastic routing inspired by a zero-range process known in statistical physics. By parameters @math and @math , this model controls degree-dependent hopping of packets and forwarding of packets with higher performance at more busy nodes. Through a theoretical analysis and numerical simulations, we derive the condition for the concentration of packets at a few hubs. In particular, we show that the optimal @math and @math are involved in the trade-off between a detour path for @math ; In the low-performance regime at a small @math , the wandering path for @math and @math is small, neither the wandering long path with short wait trapped at nodes ( @math ), nor the short hopping path with long wait trapped at hubs ( @math ) is advisable. A uniformly random walk ( @math ) yields slightly better performance. We also discuss the congestion phenomena in a more complicated situation with packet generation at each time step.Cited Abstract(s):[1]: We numerically investigate jamming transitions in complex heterogeneous networks. Inspired by Internet routing protocols, we study a general model that incorporates local traffic information through a tunable parameter. The results show that whether the transition from a low-traffic regime to a congested phase is of first- or second-order type is determined by the protocol at work. The microscopic dynamics reveals that these two radically different behaviors are due to the way in which traffic jams propagate through the network. Our results are discussed in the context of Internet dynamics and other transport processes that take place on complex networks and provide insights for the design of routing policies based on traffic awareness in communication systems.[2]: We propose a routing strategy to improve the transportation efficiency on complex networks. Instead of using the routing strategy for shortest path, we give a generalized routing algorithm to find the so-called efficient path, which considers the possible congestion in the nodes along actual paths. Since the nodes with the largest degree are very susceptible to traffic congestion, an effective way to improve traffic and control congestion, as our strategy, can be redistributing traffic load in central nodes to other noncentral nodes. Simulation results indicate that the network capability in processing traffic is improved more than 10 times by optimizing the efficient path, which is in good agreement with the analysis. DOI: 10.1103 PhysRevE.73.046108 PACS numbers: 89.75.Hc Since the seminal work on scale-free networks by Barabasi and Albert BA model1 and on the small-world phenomenon by Watts and Strogatz 2, the structure and dynamics of complex networks have recently attracted a tremendous amount of interest and attention from the physics community see the review papers 3‐5 and references therein. The increasing importance of large communication networks such as the Internet 6, upon which our society survives, calls for the need for high efficiency in handling and delivering information. In this light, to find optimal strategies for traffic routing is one of the important issues we have to address. There have been many previous studies to understand and control traffic congestion on networks, with a basic assumption that the network has a homogeneous structure 7‐11. However, many real networks display both scale-free and small-world features, and thus it is of great interest to study the effect of network topology on traffic flow and the effect of traffic on network evolution. present a formalism that can cope simultaneously with the searching and traffic dynamics in parallel transportation systems 12. This formalism can be used to optimize network structure under a local search algorithm, while to obtain the formalism one should know the global information of the whole networks. Holme and Kim provide an in-depth analysis on the vertex edge overload cascading breakdowns based on evolving networks, and suggest a method to avoid[3]: networks. The strategy is governed by a single parameter. Simulation results show that maximizing the network capacity and reducing the packet travel time can generate an optimal parameter value. Compared with the strategy of adopting exclusive local static information, the new strategy shows its advantages in improving the efficiency of the system. The detailed analysis of the mixing strategy is provided for explaining its effects on traffic routing. The work indicates that effectively utilizing the larger degree nodes plays a key role in scalefree traffic systems.[4]: We define a minimal model of traffic flows in complex networks in order to study the trade-off between topological-based and traffic-based routing strategies. The resulting collective behavior is obtained analytically for an ensemble of uncorrelated networks and summarized in a rich phase diagram presenting second-order as well as first-order phase transitions between a free-flow phase and a congested phase. We find that traffic control improves global performance, enlarging the free-flow region in parameter space only in heterogeneous networks. Traffic control introduces nonlinear effects and, beyond a critical strength, may trigger the appearance of a congested phase in a discontinuous manner. The model also reproduces the crossover in the scaling of traffic fluctuations empirically observed on the Internet.

question:You will be shown a paragraph from a biomedical research article. Your task is to extract all drug combinations appearing in a specific sentence within in the paragraph. Each drug combination should be assigned to one of the following three categories:- POS: Indicates a positive interaction between the drugs in the combination; for instance, drugs that have an additive or synergistic effect.- NEG: Indicates a negative interaction between the drugs in the combination; for instance, combining these drugs might result in adverse side effects, or might reduce their efficacy.- COMB: Indicates that the drugs are given in combination, but the type of interaction between the drugs cannot be determined based on the provided context.Please format your answer as a json array. Each entry in the array should itself be an array formatted as [<drug_1>, <drug_2>, ..., <drug_n>, <category>] where <category> is one of the three categories listed above and <drug_1>, ..., <drug_n> are drug names copied verbatim from the input sentence. Different combinations may involve different numbers of drugs; in other words, the `n` in <drug_n> may vary.As an example, the following output describes two extracted drug combinations; one between two drugs, and one between three drugs:[["artesunate", "artemether", "COMB"], ["Nifedipine", "Labetalol", "Prazosin", "POS"]]The paragraph and specific sentence are below. You should only extract relationships expressed in the specific sentence; the paragraph is provided for context.In your output, return only the json array and no other text. If no drug combinations appear, return an empty array `[]`.paragraph: Efficacy of Topical Combination of 0.25% Finasteride and 3% Minoxidil Versus 3% Minoxidil Solution in Female Pattern Hair Loss: A Randomized, Double-Blind, Controlled Study. The relationship between female pattern hair loss (FPHL) and androgenic hormones is not well established, but some evidence indicates oral finasteride may be efficacious in FPHL. Use of a topical formulation has been proposed to minimize unwanted effects. objectives Our objective was to compare the efficacy and safety of topical 0.25% finasteride combined with 3% minoxidil solution and 3% minoxidil solution as monotherapy in the treatment of FPHL. methods This was a prospective, randomized, double-blind study in 30 postmenopausal women with FPHL. Each participant was randomized to receive either topical 0.25% finasteride combined with topical 3% minoxidil or topical 3% minoxidil solution as monotherapy for 24 weeks. To determine efficacy, the hair density and diameter was measured and global photographic assessment was conducted at baseline and 8, 16, and 24 weeks. Side effects and serum dihydrotestosterone levels were also evaluated. results By 24 weeks, hair density and diameter had increased in both groups, and finasteride/minoxidil was significantly superior to minoxidil solution in terms of hair diameter (p = 0.039). No systemic side effects were reported. However, serum dihydrotestosterone levels in the finasteride/minoxidil group significantly decreased from baseline (p = 0.016). conclusion A topical combination of 0.25 % finasteride and 3 % minoxidil may be a promising option in the treatment of FPHL with an additional benefit of increasing hair diameter . Nevertheless, as it may be absorbed percutaneously, it should be reserved for postmenopausal women. Trial Registration clinicaltrials.in.th; identifier TCTR20160912002.sentence: A topical combination of 0.25 % finasteride and 3 % minoxidil may be a promising option in the treatment of FPHL with an additional benefit of increasing hair diameter .

question:Who won the men's double when Chou Tien-Chen won the men's single?| | Year | Mens singles | Womens singles | Mens doubles | Womens doubles | Mixed doubles ||---:|-------:|:-------------------------|:-----------------------|:----------------------------------------|:----------------------------------------|:--------------------------------------------|| 0 | 1988 | Kim Brodersen | Katrin Schmidt | Markus Keck Robert Neumann | Katrin Schmidt Nicole Baldewein | Markus Keck Katrin Schmidt || 1 | 1989 | Sörgard | Katrin Schmidt | Stefan Frey Robert Neumann | Birgitta Lehnert Monica Halim | Chen Jin Katrin Schmidt || 2 | 1998 | Yong Yudianto | Karolina Ericsson | Michael Keck Christian Mohr | Erica van den Heuvel Judith Meulendijks | Michael Keck Nicol Pitro || 3 | 1999 | Oliver Pongratz | Zheng Yaqiong | Quinten van Dalm Dennis Lens | Britta Andersen Lene Mork | Chris Bruil Erica van den Heuvel || 4 | 2000 | Xie Yangchun | Xu Huaiwen | Michael Søgaard Joachim Fischer Nielsen | Claudia Vogelgsang Xu Huaiwen | Michael Keck Erica van den Heuvel || 5 | 2001 | Niels Christian Kaldau | Pi Hongyan | Michael Søgaard Michael Lamp | Neli Boteva Elena Nozdran | Chris Bruil Lotte Bruil-Jonathans || 6 | 2002 | Chen Gang | Pi Hongyan | Simon Archer Flandy Limpele | Mia Audina Lotte Bruil-Jonathans | Nathan Robertson Gail Emms || 7 | 2003 | Dicky Palyama | Xu Huaiwen | Michał Łogosz Robert Mateusiak | Nicole Grether Juliane Schenk | Frederik Bergström Johanna Persson || 8 | 2004 | Niels Christian Kaldau | Xu Huaiwen | Simon Archer Anthony Clark | Kamila Augustyn Nadieżda Kostiuczyk | Rasmus Mangor Andersen Britta Andersen || 9 | 2005 | Kasper Ødum | Xu Huaiwen | Tony Gunawan Halim Haryanto | Nicole Grether Juliane Schenk | Vladislav Druzhchenko Johanna Persson || 10 | 2006 | Ronald Susilo | Xu Huaiwen | Michał Łogosz Robert Mateusiak | Jiang Yanmei Li Yujia | Robert Mateusiak Nadieżda Kostiuczyk || 11 | 2007 | Lu Yi | Wang Yihan | Mathias Boe Carsten Mogensen | Yang Wei Zhang Jiewen | Kristof Hopp Birgit Overzier || 12 | 2008 | Chetan Anand | Maria Febe Kusumastuti | Mathias Boe Carsten Mogensen | Helle Nielsen Marie Roepke | Diju Valiyaveetil Jwala Gutta || 13 | 2009 | Jan Ø. Jørgensen | Juliane Schenk | Rupesh Kumar Sanave Thomas | Helle Nielsen Marie Roepke | Mikkel Delbo Larsen Mie Schjoett-Kristensen || 14 | 2010 | Chen Long | Liu Xin | Mathias Boe Carsten Mogensen | Pan Pan Tian Qing | Zhang Nan Zhao Yunlei || 15 | 2011 | Hans-Kristian Vittinghus | Li Xuerui | Bodin Isara Maneepong Jongjit | Mizuki Fujii Reika Kakiiwa | Chan Peng Soon Goh Liu Ying || 16 | 2012 | Chou Tien-chen | Juliane Schenk | Ingo Kindervater Johannes Schoettler | Wang Rong Zhang Zhibo | Anders Kristiansen Julie Houmann |Create a SQL query to retrieve information from the table that can help answer the question.

question:If Ty has a specific time frame of 12 weeks to complete reading a number of books, and he dedicates 2 weeks to each book, what mathematical expression should Ty use to ascertain the total volume of books he can finish in that time? A) 12 - 2 B) 12 + 12 C) 12 - 2 - 2 - 2 D) 12 - 2 - 2 - 2 - 2 - 2 - 2

question:I'm working on a project with a friend that will utilize Hbase to store it's data. Are there any good query examples? I seem to be writing a ton of Java code to iterate through lists of RowResult's when, in SQL land, I could write a simple query. Am I missing something? Or is Hbase missing something?