question:You will be presented with a citation segment from the section of an NLP research paper, as well as the context surrounding that citation. Classify the intent behind this citation by choosing from one of the following categories:- Background: provides context or foundational information related to the topic.- Extends: builds upon the cited work.- Uses: applies the methods or findings of the cited work.- Motivation: cites the work as inspiration or rationale for the research.- CompareOrContrast: compares or contrasts the cited work with others.- FutureWork: cites the work as a direction for future research.Your answer should be a single word from the following list of options: ["Background", "Extends", "Uses", "Motivation", "CompareOrContrast", "FutureWork"]. Do not include any other text in your response.Section Title:experimentsContext before the citation:This is similar to the “deletion” strategy employed by Zettlemoyer and Collins (2007), but we do it directly in the grammar. If no parse is found yet, then the parser attempts to strategically allow tokens to subsume a neighbor by making it a dependent (first with a restricted root set, then without). If that fails, then it searches for a parse with any root.Citation Sentence:This is similar to the `` deletion '' strategy employed by Zettlemoyer and Collins ( 2007 ) , but we do it directly in the grammar .Context after the citation:We add unary rules of the form (D)-*u for every potential supertag u in the tree. Then, at each node spanning exactly two tokens (but no higher in the tree), we allow rules t-*((D), v) and t-*(v, (D)). Recall that in §3.1, we stated that (D) is given extremely low probability, meaning that the parser will avoid its use unless it is absolutely necessary. Additionally, since u will still remain as the preterminal, it will be the category examined as the context by adjacent constituents.

question:You will be shown biomedical passages and your task is to the answer the provided question. Provide a concise and accurate response and do not include any additional text in the response other than the answer.Question: Which was the first adeno-associated virus vector gene therapy product approved in the United States?Context: Gene therapy utilizing viral vectors has experienced recent success, culminating in U.S. Food and Drug Administration approval of the first adeno-associated virus vector gene therapy product in the United States: Luxturna for inherited retinal dystrophy.

question:You will be presented with the full text of a science research paper. Please write an abstract for this paper. Your response should include the abstract and no additional text.Paper text:from a historical point of view , fractional calculus provides us with a set of axioms and methods to extend the concept of a derivative operator from integer order n to arbitrary order @xmath0 , where @xmath0 is a real or complex value .@xmath1 in the sense of ( [ art14first ] ) fractional calculus has been frequently applied in the area of image processing , see e.g. [ @xcite ] , [ @xcite ] , [ @xcite ] .alternatively we may consider fractional calculus as a specific prescription to extend the definition of a local operator to the nonlocal case . in this lecture, we will present a covariant , multidimensional generalization of the fractional derivative definition , which may be applied to any bound operator on the riemannian space . as a first application, we will propose a specific non - local extension of the modified local laplace - operator , which is widely used in problems of image processing .we will especially compare the local to the nonlocal approach for 3d - shape recovery from a set of 2d aperture afflicted slide sequences , which may be obtained e.g. in confocal microscopy or autofocus algorithms [ @xcite ] , [ @xcite ] .it will be shown , that a major improvement of results is achieved for the nonlocal version of the modified laplace - operator .we will propose a reinterpretation of the fractional calculus as a specific procedure for a non - local extension of arbitrary local operators .for that purpose , we start with the liouville definition of the left and right fractional integral [ @xcite ] : @xmath2 with a slight modification of the fractional parameter @xmath3 , where @xmath0 is in the interval @xmath4 . consequently for the limiting case @xmath5 @xmath6 and @xmath7 both coincide with the unit - operator and for @xmath8 @xmath6 and @xmath7 both correspond to the standard integral operator .@xmath6 and @xmath7 may be combined to define a regularized liouville integral [ @xcite ] : @xmath9 where we have introduced the symmetric shift - operator : @xmath10 the regularized fractional liouville - caputo derivative may now be defined as : @xmath11 with the abbreviation @xmath12 . this definition of a fractional derivative coincides with feller s [ @xcite ] definition @xmath13 for the special case @xmath14 .we may interpret @xmath15 as a non - localization operator , which is applied to the local derivative operator to determine a specific non - local extension of the same operator .therefore the fractional extension of the derivative operator is separated into a sequential application of the standard derivative followed by a non - localization operation .the classical interpretation of a fractional integral is changed from the inverse operation of a fractional derivative to a more general interpretation of a non - localization procedure , which may be easily interpreted in the area of image processing as a blur effect .this is a conceptual new approach , since it may be easily extended to other operators e.g. higher order derivatives or space dependent operators , e.g. for @xmath16 we obtain : @xmath17 which is nothing else but the riesz [ @xcite ] definition of a fractional derivative .therefore we define the following fractional extension of a local operator @xmath18 to the non - local case @xmath19 as the covariant generalization of the liouville - caputo fractional derivative to arbitrary operators on @xmath20 .this definition may be easily extended to the multidimensional case , interpreting the variable @xmath21 as a measure of distance . in two dimensions , with @xmath22 and with @xmath23 @xmath24 explicitly reads : @xmath25 which is normalized such , that the eigenvalue spectrum for : @xmath26 with the eigenfunctions @xmath27 follows as : @xmath28 it should be noted , that the validity range for @xmath0 spans from @xmath29 , since we deal with a two - dimensional problem .obviously within the framework of signal processing , the non - localization operator may be interpreted as a low - pass filter . in the following sections, we will use this operator for a well defined extension of the standard algorithm used for 3d - shape recovery from aperture afflicted 2d - slide sequences to a generalized , fractional nonlocal version , which results in a very stable procedure with drastically reduced errors .we will first present the minimal standard method and its limitations in the next section . andright column @xmath30 ) from a 2d - slide sequence @xmath31 . from top to bottom original slide , result of local modified laplacian from ( [ lap2 ] ) @xmath32 and result of nonlocal operator are shown ., width=317 ]in a set @xmath33 of @xmath34 2d - slides with increasing focal distance @xmath35 , @xmath36 every slide contains areas with focused as well as defocused parts of the specimen considered . in the first row of fig .[ fig1 ] we present two examples from a slide - sequence of a spherical object with radius @xmath37 located at @xmath38 in the x , y - plane , where the focal plane was chosen to be @xmath39 and @xmath30 respectively . for a 3d - shape recovery in a first step for a given slidethe parts being in focus have to be extracted . for a textured object ,areas in focus are dominated by a larger amount of high frequency contributions , while for out of focus parts mainly the low frequency amount of texture survives .consequently an appropriate operator to determine the high - frequency domains is the modified laplacian @xmath40 given e.g. by : @xmath41 where @xmath42 denotes the absolute value . in the discrete case with a symmetrically discretized function @xmath43 on a rectangular domain @xmath44 and @xmath45 : @xmath46 with stepsize @xmath47 in both x- and y - direction , the same operator is given by : @xmath48 and @xmath49 elsewhere , where the free parameter @xmath50 has to be chosen according to the nyquist - shannon sampling theorem [ @xcite ] to be of order of the inverse average wavelength @xmath51 of the texture applied to the object considered @xmath52 a requirement , which can be fulfilled only locally for random generated textures and for regular textures on curved surfaces respectively .an application of the modified laplacian to every slide in a set @xmath53 leads to a set of intensity values @xmath54 at a given pixel - position at @xmath55 : @xmath56 in the second row of fig .[ fig1 ] the result of an application of the discrete modified laplacian with @xmath57 to the original slides presented in the first row , is demonstrated .it is assumed , that for a fixed @xmath50 a maximum exists in @xmath58 for a given @xmath59 . a parabolic fit of @xmath54 near @xmath59 helps to determine the position @xmath60 , where @xmath61 is maximal : @xmath62 from ( [ lap2 ] ) for different values of step - size @xmath50 .it should be noted , that there is no fixed value of @xmath50 , which uniquely may be used to determine all positions .there are drop outs for every curve .errors are listed in table [ art14tab1 ] ., width=317 ] in the center row of fig .[ fig1 ] we present the result of the application of ( [ lap2 ] ) onto the original slides .the gray - level indicates the intensity values @xmath54 for @xmath63 and @xmath64 respectively . in fig [ fig2 ]recovered @xmath65 along the positive y - axis are compared for different q - values with the original height - values .obviously there is no unique optimum choice for q , which works for all positions simultaneously .the proposed simple local approach is not very effective , instead it generates drop outs as a result of an interference of varying texture scaling with the fixed step size q. for a realistic treatment of 3d - shape recovery a more sophisticated procedure is necessary .consequently a nonlocal approach , which weights the different contributions for a varying step size is a promising and well defined approach .indeed it will enhance the quality of the results significantly , as will be demonstrated in the next section .the generalized fractional approach extends the above presented local algorithm .the nonlocal modified laplacian according to ( [ gen ] ) is given by : @xmath66 therefore we obtain a well defined two step procedure .first , the local operator is applied , followed by the nonlocalization integral . in the discrete case ,applying the nonlocal laplacian to every slide in a slide set , the first step is therefore identical with ( [ dloc ] ) and yields a set of intensity values @xmath54 at a given pixel - position at @xmath55 .an application of the discrete version of @xmath15 then leads to : @xmath67 where we have introduced a cutoff @xmath68 , which limits the integral on the finite domain of pixel values .if we interpret the intensity values as constant function values at position @xmath55 with size @xmath47 , the integration may be performed fully analytically . in the appendixwe have listed the resulting matrix - operator for @xmath69 .the resulting nonlocal intensities @xmath70 are presented in the lower row of fig .the nonlocal approach reduces the granularity of the local operator and a more smooth behaviour of intensities results . since this is the only modification of the local approach , the recovery of the height information for every pixel is similar to ( [ locz ] ) @xmath71 in fig .[ fig3 ] results are plotted for different values of @xmath0 . from ( [ genl3 ] ) for different values of the fractional parameter @xmath0 .the algorithm is very stable against a variation of @xmath0 . in the limit @xmath5 the nonlocal approach reduces to the local scenario .errors are listed in table [ art14tab1 ] ., width=317 ] l|lllll|l @xmath68 & @xmath72 & @xmath73 & @xmath74 & @xmath75 & @xmath76 & q + 1 & 0.277 & 0.265 & 0.263 & 0.405 & 1.929 & 1.929 + 2 & 0.227 & 0.225 & 0.225 & 0.301 & 1.929 & 2.496 + 3 & 0.211 & 0.211 & 0.216 & 0.272 & 1.929 & 3.702 + 4 & 0.182 & 0.187 & 0.198 & 0.251 & 1.929 & 3.702 + 5 & 0.145 & 0.151 & 0.172 & 0.235 & 1.929 & 3.945 + 6 & 0.134 & 0.136 & 0.158 & 0.223 & 1.929 & 6.131 + 7 & 0.137 & 0.138 & 0.155 & 0.215 & 1.929 & 2.832 + 8 & 0.146 & 0.143 & 0.154 & 0.205 & 1.929 & 4.228 + in table [ art14tab1 ] a listing of errors is given for the local and the nonlocal algorithm presented .we may conclude , that the nonlocal approach is very robust and stable in a wide range of @xmath0 and @xmath68 values respectively .we gain one order of magnitude in accuracy using the nonlocal modified laplacian .an additional factor 2 in accuracy is obtained if we chose the optimal fractional @xmath77 parameter set .the discrete version of the nonlocalization operator @xmath15 from ( [ genl3 ] ) may be interpreted as a matrix operation @xmath78 on @xmath43 : @xmath79 @xmath78 is a quadratic @xmath80 matrix with the symmetry properties @xmath81 setting the normalization condition @xmath82 the integral may be solved analytically for stepwise constant pixel values @xmath83 . as an example , we present the fourth quadrant of @xmath78 for @xmath69 in units @xmath47 : obviously there is a smooth transition from a local ( @xmath5 ) to a more and more nonlocal operation , which in the limiting case ( @xmath84 ) may be interpreted as the result of the use of a pinhole camera with finite hole radius @xmath68 .we thank a. friedrich and g. plunien from tu dresden , germany for useful discussions .the original 2d - slide sequence , two examples shown in the topmost row in fig [ fig1 ] , was generated using povray [ @xcite ] .99 falzon , f. and giraudon , g. ( 1994 ) ._ singularity analysis and derivative scale - space _ in proceedings cvpr 94 , ieee computer society conference,245250 .. feller , w. ( 1952 ) ._ on a generalization of marcel riesz potentials and the semi - groups generated by themuniversite de lund , 7281 .herrmann , r. ( 2011 ) ._ fractional calculus - an introduction for physicists _ world scientific publishing , singapore .liouville , j. ( 1832 ) ._ sur le calcul des differentielles @xmath85 indices quelconques_ j. @xmath86cole polytechnique * 13 * , 1162 .oldham , k. b. and spanier , j. ( 1974 ) . _ the fractional calculus _, academic press , new york .ortigueira , m. d. and machado , j. a. t. ( 2003 ) ._ fractional signal processing and applications _ , signal processing , * 83 * , 2285 - 2286 .riesz , m. ( 1949 ) ._ lintegrale de riemann - liouville et le probl@xmath87me de cauchy _ acta math . * 81 * , 1223 .povray ( 2011 ) . _ persistence of vision raytracer _ http://www.povray.org .shannon , c. e. ( 1949 ) ._ communication in the presence of noise _ , proc .inst . of radio engineers , * 37*(1 ) , 1021 .sparavigna , a. c. ( 2009 ) ._ using fractional differentiation in astronomy _ , arxiv.org:0910.2381 .spencer , m. ( 1982 ) ._ fundamentals of light microscopy _ , cambridge university press .zernike , m. ( 1935 ) ._ das phasenkontrastverfaren bei der mikroskopischen beobachtung _ z. tech* 16 * , 454457 .

question:You are presented with multiple paper abstracts, alongside the associated literature review and chapter titles. Given the provided information, you are going to do a literature review. Please generate a coherent literature review that synthesizes the content, draws connections between different works, highlights major findings, and identifies any gaps in the existing research.Literature Review Title: A Survey of Signed Network Mining in Social Media Chapter Title: Low-rank approximation methods: 1. Abstract of Cited Paper (BIB001): Online social networks continue to witness a tremendous growth both in terms of the number of registered users and their mutual interactions. In this paper, we focus on online signed social networks where positive interactions among the users signify friendship or approval, whereas negative interactions indicate antagonism or disapproval. We introduce a novel problem which we call the link label prediction problem: Given the information about signs of certain links in a social network, we want to learn the nature of relationships that exist among the users by predicting the sign, positive or negative, of the remaining links. We propose a matrix factorization based technique MF-LiSP that exhibits strong generalization guarantees. We also investigate the applicability of logistic regression [8] in this setting. Our experiments on Wiki-Vote, Epinions and Slashdot data sets strongly corroborate the efficacy of these approaches. 2. Abstract of Cited Paper (BIB002): Mobile online social network (mOSN) is a burgeoning research area. However, most existing works referring to mOSNs deal with static network structures and simply encode whether relationships among entities exist or not. In contrast, relationships in signed mOSNs can be positive or negative and may be changed with time and locations. Applying certain global characteristics of social balance, in this paper, we aim to infer the unknown relationships in dynamic signed mOSNs and formulate this sign inference problem as a low-rank matrix estimation problem. Specifically, motivated by the Singular Value Thresholding (SVT) algorithm, a compact dictionary is selected from the observed dataset. Based on this compact dictionary, the relationships in the dynamic signed mOSNs are estimated via solving the formulated problem. Furthermore, the estimation accuracy is improved by employing a dictionary self-updating mechanism.Literature Review:

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: ["AnatomicalEntity"].Please return the output as a JSON object of the format: {"AnatomicalEntity": ["tumor cells", ...]}. 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:Effects of doxycycline on in vitro growth, migration, and gelatinase activity of breast carcinoma cells.Metastatic disease is one of the major causes of death from cancer in human beings. Several enzyme systems have been implicated in the metastatic process, but the metalloproteinases (MPs) appear to be the major group involved in most instances of neoplastic invasion. Increased MP activity has been correlated with the metastatic potential of many cancers, including breast cancer. MPs also play a role in tumor angiogenesis. Tetracyclines are antimicrobial agents that can suppress MP activity in a variety of tissues, including gingiva, bone, and cartilage. Several reports have indicated that tetracyclines can suppress tumor MPs as well. A synthetic tetracycline, doxycycline, inhibits migration of human MDA-MB-435 breast adenocarcinoma cells through a reconstituted basement membrane (Matrigel), an assay used as an in vitro surrogate for the in vivo process of tumor invasion through basement membranes. Additionally, doxycycline diminishes the proliferation of this breast cancer cell line and also decreases its gelatinolytic activity, as determined by gel zymography.

question:You are presented with a paragraph from a COVID-19 literature. Classify the topics of this piece of text by choosing from the following categories:- Epidemic Forecasting: The content relates to predictions about the spread of COVID-19.- Treatment: The paragraph discusses therapeutic methods or medication for COVID-19.- Prevention: The content covers measures to prevent the spread of COVID-19.- Mechanism: The paragraph explains the biological mechanisms of the virus.- Case Report: The content is a report of a COVID-19 case.- Transmission: The paragraph discusses how COVID-19 is transmitted.- Diagnosis: The content is about diagnosing COVID-19 in individuals.Your classification should be provided as an element within a JSON array. The array should be formatted with topics enclosed in double quotes and separated by commas, following the JSON format, for example: ["Topic1", "Topic2", ...]. Include all applicable topics within the array. Your output should be a valid JSON array, and no additional text should be included in your response.Article:Recent studies have reported that COVID-19 patients with lung cancer have a higher risk of severe events than patients without cancer. In this study, we investigated the gene expression of angiotensin I-converting enzyme 2 (ACE2) and transmembrane serine protease 2 (TMPRSS2) with prognosis in lung adenocarcinoma (LUAD) and lung squamous cell carcinoma (LUSC). Lung cancer patients in each age stage, subtype, and pathological stage are susceptible to SARS-CoV-2 infection, except for the primitive subtype of LUSC. LUAD patients are more susceptible to SARS-CoV-2 infection than LUSC patients. The findings are unanimous on tissue expression in gene and protein levels.